Hire the Best Certified AWS Big Data Engineers

Clients rate our Certified AWS Big Data Engineers
Rating is 4.8 out of 5.
4.8/5
Based on 386 client reviews
M Haseeb A.

Stockholm, Sweden

$35/hr
5.0
40 jobs

Fortune 500 companies don't hire me for dashboards, they hire me to solve complex data challenges. For 16+ years, as an Official Databricks ISV Partner and Registered Snowflake Partner, I've delivered Enterprise Data Engineering, Big Data Engineering, Databricks, Snowflake, Data Visualization, and Cloud solutions for Fortune 500 companies including S&P Global, Electrolux, Hexagon, and Ernst & Young. 💼 I don't just build dashboards or pipelines, I architect scalable data platforms that process massive datasets, streamline decision-making, and give organizations the foundation they need to power analytics, AI, machine learning, and long-term business growth. 🤝 I believe Trust should be earned, not assumed. That's why I give every client a FREE 30-minute consultation and, a FREE Proof of Concept (POC). Unlike most freelancers, I don't expect you to make a decision based on promises alone. I let you see the solution first. 📩 Before you commit to the project! or spend a single dollar! I will build a working Proof of Concept tailored to your requirements. Here's what you get: ✔ See your solution before you pay ✔ FREE Proof of Concept (POC) tailored to your project ✔ FREE 30-minute consultation with actionable technical recommendations ✔ Validate the architecture and implementation approach with zero risk ✔ No obligation. No commitment. 🚀 Click "Invite to Job" to claim your FREE Consultation & FREE POC. ⭐ What My Clients Says About Me: ⚡ "Exceptional expertise in Snowflake, data pipeline development, ETL/ELT, Python, SQL, and Big Data technologies throughout the project." ⚡ "I was impressed by Haseeb's work on data modeling, optimization, and automation. Strong technical expertise and great communication throughout." ⚡ "Haseeb not only completed the project on time but also compiled a full report on the architecture and a presentation to walk me through the key information." ⚡ "An exceptional ETL data pipeline developer. His attention to detail and problem-solving skills were impressive." ⚡ "Professional, reliable, solution-oriented, and committed to quality." Is your business facing any of these challenges? 🚫 You're collecting more data but getting less value from it. 🚫 Your business has no solid data foundation to support AI, analytics, or future growth. 🚫 Slow ETL & Data Pipelines are delaying critical decisions. 🚫 Data is scattered across multiple systems with no single source of truth. 🚫 Underperforming Databricks or Snowflake environments. I've spent 16+ years solving exactly these problems for enterprise teams. Data Engineering Services: ✔ Databricks & Snowflake ✔ Apache Spark & PySpark Development ✔ Delta Lake ✔ Delta Live Tables ✔ ETL / ELT Pipeline Development ✔ Data Pipeline Automation ✔ Data Platform Architecture ✔ Data Warehouse ✔ Data Lake ✔ BigQuery ✔ SQL ✔ Data Modeling ✔ Data Governance ✔ Cloud Data Migration ✔ Azure ✔ AWS ✔ GCP ✔ Apache Kafka ✔ Apache Flink ✔ Real-Time Streaming Pipelines ✔ Analytics Engineering Data Visualization & Business Intelligence Services: ✔ Power BI Dashboards ✔ Interactive Data Visualization ✔ Executive KPI Dashboards ✔ Operational Dashboards ✔ Business Intelligence Solutions ✔ Looker Studio ✔ Automated Reporting ✔ Business Analytics ✔ Financial Reporting Dashboards ✔ Sales & Marketing Dashboards ✔ Real-Time Analytics Dashboards Why clients choose me ✅ 16+ years in Enterprise Data Engineering ✅ Fortune 500 experience (S&P Global, Electrolux, Hexagon, EY) ✅ CEO & Co-Founder of a specialized AI, Cloud & Data consultancy ✅ AWS Certified Data Engineer ✅ Databricks implementation expert ✅ Apache Spark & PySpark specialist ✅ Apache Kafka & Apache Flink expertise ✅ Open-source contributor ✅ End-to-end ownership, from strategy to deployment Industries I've Worked With • Manufacturing • Financial Services • Enterprise SaaS • Industrial IoT • Smart Devices • Real Estate • Energy • Retail • AI & Data Platforms Core expertise: Big Data Engineer • Data Engineer • Databricks • Apache Spark • PySpark • Snowflake • Delta Lake • Delta Live Tables • Unity Catalog • Azure • AWS • GCP • Azure Data Factory • AWS Glue • BigQuery • SQL • Python • Power BI • Looker Studio • Apache Kafka • Apache Flink • ETL • ELT • Data Engineering • Big Data • Data Architecture • Data Modeling • Data Warehouse • Data Lake • Streaming Data • Data Governance • Business Intelligence • Data Visualization • Cloud Migration • Analytics Engineering 🚀 Let's start with a FREE consultation. Tell me about your data challenges, business goals, or existing platform. I'll provide a FREE consultation and a FREE Proof of Concept (POC) so you can evaluate the solution before making any commitment. Click "Invite to Job" and let's discuss how we can bring your vision to life

  • Big Data
  • Python
  • ETL
  • Data Engineering
  • Snowflake
  • Machine Learning
  • ETL Pipeline
  • Database Architecture
  • Data Processing
  • Database Design
  • Data Analysis
  • Cloud Engineering
  • Data Analytics & Visualization Software
  • Data Warehousing & ETL Software
  • BigQuery
  • Data Integration
  • Databricks Platform
  • Database
  • Data Analytics
  • Apache Flink
Adnan A.

Ely, United Kingdom

$90/hr
5.0
15 jobs

I help organisations turn AI ideas into secure, scalable, production-ready solutions. I am an Expert-Vetted AI consultant, AI leader and PhD-qualified machine learning specialist with more than 12 years of experience delivering AI, machine learning and generative AI solutions across enterprise, startup, healthcare, education and technology environments. My work covers the full AI lifecycle—from strategy and solution architecture through rapid prototyping, production deployment, MLOps, governance and adoption. How I can help ▪ Generative AI and AI agents RAG applications, enterprise copilots, agentic workflows, document intelligence, LLM evaluation and secure deployment. ▪ AI strategy and technical advisory AI roadmaps, use-case prioritisation, architecture reviews, build-vs-buy decisions, vendor evaluation and fractional CTO support. ▪ Machine learning solutions Prediction, recommendation, personalisation, classification, forecasting and optimisation systems. ▪ Cloud AI architecture Production-grade solutions using Google Cloud, AWS and Azure, including Vertex AI, BigQuery, Cloud Run, SageMaker, Bedrock and associated data services. ▪ MLOps and LLMOps Automated training and deployment pipelines, monitoring, evaluation, model governance, CI/CD and responsible AI controls. Selected outcomes - Built and led an AI and data science function, growing the team from 3 to 15 people - Delivered AI initiatives generating millions in measurable value - Deployed generative AI solutions that improved operational efficiency by 35% - Developed machine learning systems that increased enrolment by 6% and associated revenue by 10% - Reduced model deployment time by approximately 50% through reusable MLOps frameworks - Supported startups as a fractional CTO, helping convert early-stage concepts into working MVPs and investor-ready technical roadmaps Recognition - DataIQ Future Leader 2025 - Winner, HESPA Innovation Award 2025 - Finalist, DataIQ Most Innovative Use of AI in Europe - Endorsed as a Data Science Leader by the Royal Academy of Engineering I combine hands-on technical depth with executive-level communication. I can work directly with engineers and data scientists, while also translating complex AI decisions into clear commercial recommendations for founders, directors and senior stakeholders. Typical engagements include AI discovery workshops, architecture design, GenAI prototypes, production implementations, technical due diligence, fractional AI leadership and ongoing advisory support.

  • Deep Learning
  • Machine Learning
  • Azure Machine Learning
  • Apache Spark MLlib
  • Databricks Platform
  • Python
  • Data Science
  • Python Scikit-Learn
  • Data Science Consultation
  • Apache Spark
  • Microsoft Azure
  • Statistical Analysis
  • Artificial Intelligence
Raghunathan S.

Puducherry, India

$30/hr
4.7
159 jobs

🥇 Top 3% AWS Expert on Upwork | AWS Advanced Tier Services Partner | Certified Solutions Architect I help startups and enterprises design, migrate, and optimize secure, scalable AWS infrastructure. 10+ years delivering cloud architecture, zero-downtime migrations, DevOps automation, and cost optimization for telecom, SaaS, fintech, and enterprise platforms handling millions of users. What I Do: ☁️ AWS Cloud Architecture – Landing Zone design, secure 3-tier architecture, multi-account strategy, high availability, disaster recovery, network design (VPC, Route53, CloudFront) 🚀 AWS Migration – Data center to AWS, multi-cloud strategy, phased migrations, zero-downtime cutover, lift-and-shift, refactor, re-platform approaches ⚙️ DevOps & Automation – Terraform IaC, CloudFormation, CI/CD pipelines (GitHub Actions, CodePipeline, Jenkins), EKS/ECS, Docker, Kubernetes, infrastructure automation 💰 AWS Cost Optimization – Right-sizing analysis, Reserved Instances, Savings Plans, FinOps implementation, cost anomaly detection, cloud billing analysis (25-40% savings achieved) 🔐 Security & Compliance – IAM hardening, least-privilege access, VPC security, WAF/Shield, encryption (KMS), SOC 2, HIPAA, PCI-DSS compliance on AWS 🤖 Serverless & AI – Lambda, API Gateway, Bedrock, SageMaker, event-driven architectures, real-time analytics AWS Services Expertise: EC2, S3, RDS, Aurora, Lambda, API Gateway, DynamoDB, ECS, EKS, CloudFront, Route53, VPC, IAM, CloudWatch, CloudTrail, Glue, Kinesis, SageMaker, Bedrock, WAF, KMS, Terraform, Docker Proven Results: ✔ Reduced AWS costs by 35% for telecom infrastructure migration ✔ Optimized video platform infra saving $7K/month in CDN + storage ✔ Migrated 20+ production workloads with zero downtime ✔ Designed secure, compliant AWS architecture for enterprise deployments ✔ Built automated DevOps pipelines reducing deployment time by 70% Why Hire Me: ⭐ Deep AWS expertise (Advanced Tier Partner certified) ⭐ Hands-on experience with enterprise workloads ⭐ Security-first architecture by design ⭐ Cost-conscious optimization without sacrificing performance ⭐ Clear architecture documentation + ongoing support ⭐ Business-focused – align cloud solutions with business goals Services: AWS architecture design, migration planning, cost optimization audit, landing zone setup, DevOps automation, infrastructure security review, compliance implementation, disaster recovery planning. Need AWS architecture advice, migration strategy, or cost optimization? Message me for a quick audit + architecture recommendation call.

  • Amazon Web Services
  • Docker
  • DevOps
  • Terraform
  • Backup & Migration
  • Migration
  • Cloud Computing
  • AWS Lambda
  • AWS Fargate
  • AWS CloudFormation
  • AWS CloudFront
  • AWS Development
  • AWS Server Migration
  • Amazon S3
  • Amazon EC2
  • Amazon ECS
  • Amazon RDS
  • Amazon Bedrock
  • Amazon Aurora
  • Amazon Redshift
Leo R.

Curitiba, Brazil

$40/hr
4.1
11 jobs

You probably think clicking "deploy" on Databricks from the cloud marketplace is all it takes to build a modern data stack. Instead, you get unmanageable infrastructure, skyrocketing costs, and pipelines feeding reports nobody trusts. 𝗜 𝗳𝗶𝘅 𝘁𝗵𝗮𝘁. 𝗡𝗼 𝗮𝗴𝗲𝗻𝗰𝗶𝗲𝘀, 𝗻𝗼 𝗯𝗹𝗼𝗮𝘁. Just a multi-certified, 5+ years of experience Cloud Solutions Architect building automated, high-integrity platforms that turn raw data into a competitive advantage. If you shoot me a invitation or message I'll send you a personalized Loom video back on how I may be able to help you; and of course, to prove that I'm the real deal, 𝗻𝗼 𝗔𝗜 𝗶𝗻𝘃𝗼𝗹𝘃𝗲𝗱! Whether you are building a greenfield lakehouse from scratch or migrating legacy systems to the cloud, I architect efficient, cost-effective environments that scale without the overhead. I understand the business bottom line just as well as the underlying code. ✪ 100% Job Success Score | 5.0★ average ✪ Proven experience on multi-cloud architectures 💡 𝗪𝗵𝗮𝘁 𝗜 𝗱𝗼: • 𝗗𝗮𝘁𝗮 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: I build production-ready environments using Terraform. No manual marketplace or standard deployments that break at scale. • 𝗥𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: Raw data becomes actionable. I build resilient Medallion architectures and automated ETL/ELT pipelines so your stakeholders actually trust the numbers. • 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗠𝗟𝗢𝗽𝘀: I bridge the gap between data engineering and machine learning. Using MLflow and Databricks Model Serving, I operationalize models into scalable, real-time REST endpoints and automated streaming inference pipelines. • 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 & 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Proper data governance utilizing Unity Catalog (no legacy Hive metastores) to ensure your data is accessible, secure, and future-proof. • 𝗖𝗹𝗼𝘂𝗱 𝗖𝗼𝘀𝘁 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Most companies overspend on cloud infrastructure. I architect systems that pay for themselves in weeks by eliminating overhead and inefficiencies with efficient auditing and monitoring features. ✅ 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 (𝘃𝗲𝗿𝗶𝗳𝗶𝗲𝗱): • Databricks Professional Data Engineer • Databricks Associate Data Engineer • Databricks Lakehouse Fundamentals • GCP Professional Data Engineer • GCP Associate Cloud Engineer • GCP Cloud Digital Leader • AWS Associate Solutions Architect • AWS Cloud Practitioner 🔧 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗖𝗹𝗼𝘂𝗱 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀: • 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀: Workflows, LDP (Lakeflow Declarative Pipelines), Unity Catalog, Workflows, Databricks SQL, MLFlow. • 𝗔𝗺𝗮𝘇𝗼𝗻 𝗪𝗲𝗯 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 (𝗔𝗪𝗦): EMR, Athena, Redshift, Glue, S3, RDS, Kinesis Data Firehose, Kinesis, and Data Streams. • 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗹𝗼𝘂𝗱 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 (𝗚𝗖𝗣): Bigquery, Dataform, Composer, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Functions, and Looker Studio. • 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗔𝘇𝘂𝗿𝗲: Data Factory, Synapse, and Storage Account. • 𝗢𝘁𝗵𝗲𝗿𝘀: Terraform, dbt, Airflow, Airbyte, Hadoop, and Hive. ⚙️ 𝗖𝗼𝗿𝗲 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: • 𝗥𝗼𝗹𝗲𝘀: Data Architect, Data Engineer, Solutions Architect, Platform Engineer • 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: Databricks (Delta Lake, Unity Catalog, Lakeflow, Workflows), BigQuery • 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: Infrastructure as Code (IaC), Terraform, Multi-Cloud (AWS, GCP, Azure) • 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: Medallion Architecture, Data Lakehouse, Data Governance, Data Quality, Machine Learning • 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: PySpark, Python, SQL, dbt, Apache Airflow, ETL/ELT, CDC, Batch and Stream Processing

  • Amazon Web Services
  • Cloud Architecture
  • Cloud Computing
  • Databricks Platform
  • Data Engineering
  • Python
  • SQL
  • PySpark
  • Apache Airflow
  • Google Cloud Platform
  • Microsoft Azure
  • ETL
  • Data Analysis
  • Bash
  • Data Modeling
  • Data Warehousing
  • Continuous Improvement
Danish V.

Mithi, Pakistan

$25/hr
4.8
83 jobs

Most data problems show up the same way, whether it's a spreadsheet someone updates by hand every week or a pipeline that's quietly started giving numbers nobody trusts. I build and fix ETL pipelines, warehouses, and API integrations on GCP and AWS, from replacing manual copy-paste with automated pulls to cutting a client's warehouse costs by ~50%. Tell me what's manual or what feels off, and I'll give you a straight read on what it'll take to fix it. Over the last 3 years I've delivered 55+ data projects across finance, healthcare, energy, and e-commerce, from one-off ETL jobs to platforms processing billions of records a day. I work GCP-first (BigQuery, Airflow, dbt, Dataflow), and I'm comfortable across AWS, Postgres, and the messy real-world stack most teams actually have. What I build: - End-to-end ETL/ELT pipelines in Python, SQL, Airflow, and dbt - BigQuery / Snowflake / Redshift warehouses and data models that stay clean as they grow - Migrations off legacy jobs and on-prem databases — without losing data in the move - Metabase, Looker Studio, and Power BI dashboards your team will actually open - Query and cost optimization when your warehouse bill stops making sense - API integrations with proper logging, retries, and checkpoints, so failures are visible instead of silent You probably need me if: - Your pipelines break and you hear it from a stakeholder, not an alert - Reports run slow, cost too much, or quietly disagree with each other - A previous developer left and nobody fully understands the setup anymore - You're scaling fast and the current data stack is starting to crack A few real results: - Architected pipelines processing 5B+ records daily at 99% reliability - Cut a client's warehouse costs ~50% by migrating legacy jobs to BigQuery - 4× throughput and 70% faster ingestion on an API pipeline pulling 2K+ domains a day - 40% faster pipeline runs through Airflow optimization How I work: a clear yes/no on feasibility before you commit, regular updates, and no disappearing mid-project. Most clients come back — usually because fixing one thing surfaces the next. If that sounds like your situation, send a short note on what's breaking or what you're trying to build, and I'll tell you straight what it'll take.

  • Big Data
  • Amazon Web Services
  • Python
  • Data Engineering
  • SQL
  • Google Cloud Platform
  • BigQuery
  • Apache Airflow
  • dbt
  • MySQL
  • Amazon Redshift
  • PySpark
  • ETL Pipeline
  • Data Warehousing
  • API
  • Spreadsheet Skills
  • Automation
  • Cloud Database
  • MySQL Programming
  • PostgreSQL
Rafay R.

Karachi, Pakistan

$20/hr
5.0
22 jobs

Over the past 5 years I've solved AWS infrastructure issues that had stumped engineering teams, built and managed complete AWS environments from the ground up, designed cross-account AWS architectures, audited enterprise cloud environments, reduced AWS costs and built serverless systems from scratch. 𝗨𝗽𝘄𝗼𝗿𝗸 𝗧𝗼𝗽 𝗥𝗮𝘁𝗲𝗱 • 𝗔𝗪𝗦 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 I've worked on cloud infrastructure powering SaaS platforms used by organizations including Novartis, Roche, UBS, Bayer and Juventus. I mostly work with startups and growing SaaS companies, but I'm equally comfortable working with established teams on architecture, DevOps and production infrastructure. 𝙒𝙝𝙖𝙩 𝙘𝙡𝙞𝙚𝙣𝙩𝙨 𝙨𝙖𝙮 "Rafay was thorough, fast, and communicated well at every stage. He also suggested improvements that helped the long-term sustainability of the project." "We had an unexpected security issue that someone else had handled poorly. Rafay quickly identified the problems, fixed them, documented everything, and even suggested improvements to prevent future issues." 𝙍𝙚𝙘𝙚𝙣𝙩 𝙋𝙧𝙤𝙟𝙚𝙘𝙩𝙨 ➜ Architected and automated cross-account AWS replication for a Swiss SaaS platform, designing IAM, EventBridge and Lambda automation across 173 production workloads under AWS Security Team review. ➜ Designed secure IAM and AWS Secrets Manager architecture for financial trading infrastructure processing over $1M/day, strengthening credential management and cloud security. ➜ Audited a 21-service AWS ECS Fargate environment, identifying approximately $25K/year in optimization opportunities while improving performance and reducing cloud costs. ➜ Deployed and stabilized an enterprise cybersecurity automation platform on bare-metal infrastructure, diagnosing a critical Docker Compose race condition and contributing the fix to the upstream open-source project. 𝘾𝙤𝙧𝙚 𝙀𝙭𝙥𝙚𝙧𝙩𝙞𝙨𝙚 ➜ AWS Solutions Architecture & Cloud Infrastructure ➜ DevOps & Platform Engineering ➜ Infrastructure as Code & Cloud Automation (Terraform, CloudFormation) ➜ Cloud Migration & Lift-and-Shift ➜ CI/CD & Release Engineering (GitHub Actions, GitLab CI, Jenkins, CircleCI, AWS CodePipeline) ➜ Docker, Kubernetes, ECS, EKS, Fargate, Helm & GitOps ➜ Deployment Strategies (Blue/Green, Rolling, Canary & Zero-Downtime Deployments) ➜ AWS Compute & Serverless (EC2, Lambda, API Gateway, EventBridge, Elastic Beanstalk, S3) ➜ AWS Networking (VPC, Public/Private Subnets, NAT Gateway, VPN & Load Balancing) ➜ CloudFront, Route 53 & Cloudflare ➜ AWS Security & DevSecOps (IAM, Secrets Manager, WAF & Firewalls) ➜ AWS Databases (RDS, Aurora, DynamoDB, PostgreSQL, MySQL, MongoDB Atlas) ➜ Monitoring, Logging, Observability (CloudWatch, Prometheus, Grafana, ELK Stack) ➜ High Availability, Incident Response, Disaster Recovery, Backup Automation ➜ Cloud Cost Optimization & FinOps ➜ React, Node.js, Next.js, Laravel, FastAPI, Linux, Python, Go, Java, JavaScript, TypeScript & Bash -- I honestly prefer conversations over long sales pitches, so if you think I'd be a good fit for your project, let's have a chat and see if we're on the same page. --

  • Amazon Web Services
  • DevOps
  • Cloud Engineering
  • Docker
  • AWS Development
  • Kubernetes
  • AWS Lambda
  • Terraform
  • Amazon ECS
  • Infrastructure as Code
  • CI/CD
  • GitHub
  • Python
  • NGINX
  • AWS CloudFront
  • Amazon RDS
  • Amazon EC2
  • Amazon DynamoDB
  • Amazon S3
  • Amazon API Gateway

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What does a Certified AWS Big data engineer do?

A certified AWS big data engineer architects and builds scalable data pipelines that ingest, store, process, and visualize massive datasets on the Amazon Web Services cloud. This specialist selects specific collection systems based on data change frequency and type to support complex analytical workloads. They design storage structures and define access patterns to optimize retrieval speeds for downstream applications. The role requires deep knowledge of security controls, including encryption and governance, to maintain data integrity across the entire lifecycle.

  • Design and implement big data architectures using services such as Amazon EMR for distributed processing and Amazon Redshift for data warehousing. The engineer chooses the right processing technology to handle batch or streaming workloads and defines operational characteristics that keep costs predictable while maintaining performance standards.
  • Build automated mechanisms that support continuous data analysis by integrating tools like Amazon Kinesis for real-time streaming and Amazon Athena for serverless querying. This work involves writing code that transforms raw inputs into structured formats, allowing business teams to run queries without managing underlying infrastructure or waiting for manual updates.
  • Apply strict data security requirements by configuring encryption at rest and in transit, establishing governance policies, and meeting compliance with regulatory standards. The engineer creates visualization delivery platforms using Amazon QuickSight to present analysis results clearly, optimizing the operational characteristics so stakeholders can interpret trends and make decisions based on accurate, secure information.

How to hire a Certified AWS Big data engineer on Upwork

Step 1: Post a job

Specify your needs for designing and implementing AWS big data services to attract qualified engineers. Use the Job Post Generator powered by Uma™, Upwork's Mindful AI to draft a precise description in seconds. Describe your requirements in a few sentences, and Uma creates a tailored post for this role. You can write a new post, update a saved draft, or reuse an existing post.

  • Request experience with Amazon EMR, Redshift, and Kinesis for processing large datasets.
  • List required skills in designing secure storage structures and defining access patterns.
  • Include expectations for building automated analysis solutions and visualization platforms.

Step 2: Evaluate candidates

Look for portfolios that demonstrate end-to-end big data lifecycle management. Uma runs instant video interviews and builds shortlists with side-by-side comparisons to speed up your review. Focus on candidates who show concrete examples of optimizing operational characteristics.

  • Verify past work involving complex data collection systems based on change frequency.
  • Check for implemented security controls including encryption and regulatory compliance.
  • Review delivered visualization dashboards built with tools like Amazon QuickSight.

Step 3: Interview your top choices

Discuss specific architectural decisions and data governance strategies during interviews. Schedule and conduct these conversations within Upwork Messages, which generates an immediate transcript and summary after each session. This keeps your hiring process organized and referenceable.

  • Ask how they choose processing technologies for specific data types and volumes.
  • Request examples of automating data analysis workflows to reduce manual effort.
  • Evaluate their approach to maintaining data integrity across distributed systems.

Step 4: Agree on scope and begin work

Set clear milestones for architecture design and implementation phases. Use Upwork Messages and the contract workroom for all communication and project management tasks. Identity verification, payment protection, hourly tracking, and project funds add security to your engagement.

  • Define deliverables for data processing pipelines and analytical solution outputs.
  • Establish timelines for deploying visualization platforms and reporting tools.
  • Confirm security protocols for encryption and governance before starting development.

Upwork is not affiliated with and does not sponsor or endorse any of the tools or services discussed in this article. These tools and services are provided only as potential options, and each reader and company should take the time needed to adequately analyze and determine the tools or services that would best fit their specific needs and situation.

The rates and information provided in this article are based on current data and industry sources available at the time of publication. Freelance rates can vary depending on factors such as experience, location, project scope, and market conditions. Readers are encouraged to conduct their own research to confirm current rates and trends, as this information may change over time.

How much does hiring a Certified AWS Big data engineer cost?

$500-$2,500 per project is a typical range for focused Certified AWS Big data engineer work. Final pricing depends on scope, technical complexity, required integrations, source-material quality, revision needs, and the freelancer's experience level.

Data security audit

$500-$1,200/project

Entry-level to mid-level
  • Review of encryption and governance controls
  • Documentation of regulatory alignment gaps
  • Steps to fix identified security issues

Storage architecture design

$1,200-$2,500/project

Mid-level
  • Schema for data formats and access patterns
  • Plan for data ingestion based on frequency
  • Methods for efficient data access and query

Processing pipeline build

$2,500-$5,000/project

Mid-level to senior-level
  • Configured Amazon EMR environment for processing
  • Code to automate data analysis workflows
  • Guide for maintaining processing characteristics

Analytics solution integration

$5,000-$8,500/project

Senior-level
  • Built and optimized data warehouse instance
  • SQL scripts for serverless data analysis
  • Real-time data collection and processing flow

End-to-end visualization platform

$8,500-$15,000/project

Expert-level
  • Interactive visualizations for business insights
  • Integrated system from collection to display
  • Optimization of operational characteristics

Frequently asked questions

Is hiring a Certified AWS Big data engineer worth it?

For most businesses, yes: hiring a Certified AWS Big data engineer is worthwhile. This certification validates the ability to design secure architectures and automate complex data pipelines using services like Amazon EMR and Amazon Kinesis. You gain a specialist who builds compliant storage structures and optimizes processing costs rather than guessing at configuration.

How do I evaluate Certified AWS Big data engineer candidates?

Evaluate candidates by asking them to describe how they select collection systems based on data change frequency and type. A strong candidate explains their choice of Amazon Redshift or Amazon Athena for specific query patterns and details how they apply encryption and governance controls to meet regulatory requirements.

What tools does a Certified AWS Big data engineer use?

These engineers build solutions using Amazon EMR for processing, Amazon Kinesis for real-time streaming, and Amazon QuickSight for visualization. They also configure Amazon Athena for serverless querying and manage storage access patterns across the data lifecycle.

What deliverables can I expect from a Certified AWS Big data engineer?

You receive implemented data processing solutions, automated analysis mechanisms, and a defined security approach covering encryption and integrity. The engineer also submits visualization platform designs that optimize how your team accesses and interprets analysis results.