Hire the Best IBM InfoSphere DataStage Specialists

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Shivam W.

Shahdara, India

$20/hr
5.0
7 jobs

I'm a Senior Data Engineer with 4.5+ years of experience building scalable, cloud-native data platforms that turn raw data into reliable, business-ready insights. I've delivered enterprise solutions across banking (NAB), healthcare (Molina), and CPG (PepsiCo), specializing in end-to-end pipeline architecture, data modeling, and cloud migrations. What I bring to your project: 🔹 Cloud Data Engineering – Deep expertise in Azure (Databricks, Data Factory, Synapse) and AWS (EMR, Glue, S3, RedShift), with hands-on migration experience from on-prem and Teradata to cloud. 🔹 Pipeline Architecture & ETL – I design and build robust ingestion frameworks handling batch, incremental, and real-time data (Event Hub, Kafka) across formats like JSON, CSV, Parquet, and fixed-width files. 🔹 Data Modeling & Warehousing – Skilled in dimensional modeling, Data Vault, star/snowflake schemas, and silver/gold layer design. I've modeled 50+ tables across Oracle Fusion, SAP S/4, and healthcare domains. 🔹 Transformation & Orchestration – I translate complex business rules into DBT models, orchestrate workflows with Apache Airflow or AutoSys, and automate CI/CD via Jenkins and Azure DevOps. 🔹 Performance & Governance – I tune PostgreSQL and Spark jobs, implement data quality checks, reconciliation frameworks, and ensure compliance with data governance standards. 🔹 Generative AI & MLOps – Databricks-certified in Generative AI, with experience integrating MLflow for experiment tracking and building LLM-based automation using OpenAI and LangChain. Tech Stack: Python | SQL | Scala | Apache Spark | DBT | PostgreSQL | Snowflake | Airflow | Databricks | Azure | AWS | Git | Jenkins | MLflow | Power BI Certifications: Databricks Certified Data Engineer Professional | Azure Data Engineer (DP-203) | Snowflake SnowPro Core | Fabric Analytics Engineer (DP-600) | Generative AI Engineer Associate Whether you need a production-grade pipeline, a cloud migration, or a well-modeled data warehouse, I deliver clean, documented, and scalable solutions — on time and with clear communication. Let's discuss your project!

  • Data Extraction
  • Data Mining
  • Artificial Intelligence
  • ETL Pipeline
  • Machine Learning
  • Database Design
  • Database Modeling
  • PySpark
  • Databricks Platform
  • Snowflake
  • Data Warehousing
  • Apache Airflow
  • Python
  • Web Scraping
  • Data Engineering
  • Generative AI
  • Exploratory Data Analysis
  • Scala
  • Data Integration
Mochammad Arie N.

Jakarta, Indonesia

$15/hr
5.0
7 jobs

Most data pipelines don’t fail because of code. They fail because they weren't built for scale. With 5+ years of experience engineering data systems at companies like Danone and Zurich, I help businesses transform fragile prototypes into resilient, production-grade infrastructure. I don’t just move data; I build the "Source of Truth" that leadership and AI systems actually trust. ➔ Productionizing AI Pipelines: Hardening Python prototypes into scalable RAG and LLM infrastructures (Azure). ➔ Infrastructure-as-Code: Building automated, modular ETL/ELT pipelines that don't require daily manual fixes. ➔ The "One-Source" Dashboard: Integrating messy data from APIs, SaaS (Shopify, HubSpot), and databases into clean Snowflake/BigQuery layers. ➔ Performance Recovery: Optimizing slow SQL queries and high-cost cloud warehouses to save you thousands in monthly spend. ➔ Technical Writing for Data & AI Teams: Creating product documentation, implementation guides, architecture documentation, data dictionaries, knowledge bases, and thought leadership content that makes complex systems easier to understand and adopt. 🛠 Tech Stack Languages: Python (FastAPI, Pandas, PySpark), SQL Data Engineering: ETL/ELT Pipelines, Data Warehousing, Data Modeling, Data Quality, Data Governance Cloud & Warehousing: Snowflake, BigQuery, Databricks, Azure Data Factory, Azure Data Lake, AWS (S3, Athena, Glue) Orchestration & Transformation: Apache Airflow, dbt Analytics & BI: Tableau, Power BI Development & Collaboration: Git, GitHub, VS Code Data Ops: API Integrations, Data Validation, Workflow Automation Technical Writing: Product Documentation, API Documentation, User Guides, Knowledge Bases, Data Dictionaries, Technical Blog Content ✅ Why Me? 5+ Years Experience: I've seen what breaks at the enterprise level and how to prevent it in your startup. Hands-On Builder & Technical Writer: I can both build the system and explain it clearly to engineers, stakeholders, and customers. Speed over Perfection: I focus on shipping high-impact systems that drive revenue, not just technical documentation. Transparent Communication: You get regular updates and a partner who challenges requirements to find better solutions. Ready to clean up your data debt?

  • Data Engineering
  • Python
  • SQL
  • ETL Pipeline
  • Databricks Platform
  • Snowflake
  • dbt
  • Apache Airflow
  • BigQuery
  • Data Migration
  • LLM Prompt
  • AI Content Writing
  • Microsoft Power BI
  • Machine Learning
  • Microsoft Azure
  • Data Warehousing & ETL Software
  • Technical Writing
  • Microsoft Power Automate
  • Data Warehousing
  • Azure Service Fabric
Vignesh B.

Chennai, India

$50/hr
5.0
5 jobs

Senior Data Architect trusted by NASA, the UN, and Mayo Clinic. I design and build production-grade data platforms, real-time streaming pipelines, and scalable analytics solutions. From high-throughput ETL/ELT pipelines to enterprise-scale data lakes, I build secure foundations for modern business intelligence and AI agents with a flawless 100% Job Success rate. If you are looking for a basic SQL scriptwriter, I am not the right fit. I specialize in complex digital transformation, big data architecture, and cost-optimized cloud infrastructure built for enterprise-scale reliability. 🚀 PROVEN CREDIBILITY * Enterprise Portfolio: Trusted to architect mission-critical data ecosystems for NASA, the United Nations, GE, Alstom, Mayo Clinic, Kaiser Permanente, United Health, and Certainti.ai. * Flawless Performance: 100% Job Success Score with consistent 5-star validation from technical stakeholders and data leaders. * AI-Ready Infrastructure: Expert at structuring raw, fragmented data into highly optimized vector data stores and clean pipelines ready for enterprise AI deployment. 📊 ENTERPRISE DATA ENGINEERING SERVICES * End-to-End Data Platforms: Architectural design and execution of data warehouses, modern data lakes, and centralized lakehouses from MVP to production scale. * Robust ETL/ELT Pipelines: Designing automated, resilient, and optimized data movement workflows to eliminate data silos. * Real-Time Data Streaming: Deploying low-latency, real-time data ingestion and processing layers for instant business insights. 🛠️ TECHNICAL CORE & CLOUD ECOSYSTEM * Cloud Data Warehouses: Snowflake, AWS Redshift, Azure Synapse, Microsoft Fabric, OneLake. * Big Data & Streaming: Apache Spark, PySpark, Apache Kafka, Databricks. * BI & Analytics: Power BI, Tableau, advanced data modeling, and robust data governance frameworks. Let’s connect to discuss how we can optimize your data infrastructure for scale, speed, and AI readiness.

  • ETL
  • Snowflake
  • Big Data
  • Data Lake
  • Python
  • Data Visualization
  • Data Warehousing
  • Microsoft Power BI
  • Azure Service Fabric
  • Databricks Platform
  • Amazon Athena
  • Amazon Bedrock
  • Google Dataflow
  • Amazon QuickSight
  • Amazon Redshift
  • AWS Glue
  • Microsoft Power BI Data Visualization
  • Google AutoML
  • Airtable
Prakash S.

Madurai, India

$25/hr
5.0
7 jobs

If your IBM i (AS400) or Mainframe system runs mission‑critical operations, you need modernization without risk I help organizations stabilize, modernize, and integrate legacy IBM i / Mainframe applications while preserving uptime, performance, and business logic. My approach focuses on incremental, low‑risk modernization—extending system life while enabling web, API, cloud, and AI‑driven innovation. With deep hands‑on experience across RPG, COBOL, Mainframe technologies, EDI integrations, and modern web stacks, I provide senior‑level ownership from assessment through production support. What I Bring IBM i / AS400: IBM i (AS400), iSeries, IBM Power Systems (V5R3–V7R5) — system modernization, application migration, performance optimization, and production stability. RPG & ILE: RPG Free, RPGLE, SQLRPGLE, RPG II–IV, CLLE, ILE — legacy refactoring, modularization, DB2 optimization, DDS‑to‑SQL migration. COBOL & Mainframe: COBOL, NetCOBOL, Fujitsu COBOL, CICS, JCL, DB2, VSAM — mainframe modernization, batch migration, performance tuning, controlled legacy transformation. Integration & Modernization: AS400 green‑screen to web (Profound UI, LANSA, SYNON, Rocket Aldon), APIs, EDI (ANSI X12, EDIFACT), ERP & Manhattan WMS integration, ESB, JSON, hybrid/cloud modernization, Angular & React frontends. AI‑Assisted Modernization: AI‑based code analysis, documentation, refactoring, anomaly detection, and batch/workflow automatio Services AS400 & Mainframe Modernization | RPG & COBOL Migration Green Screen to Web Conversion | EDI & API Integration DB2 & Data Migration | Production Support & Maintenance Skills & Technologies Languages: RPG, RPGLE, RPG Free, COBOL, NetCOBOL, JCL, SQL, Python, Java, PHP Databases: DB2/400, IBM Db2, VSAM, PostgreSQL, MS SQL Tools: Profound UI, LANSA, SYNON, Presto, Rocket Aldon, RDz, Eclipse Source Control: Aldon, Turnover, Implementer, Endevor, Git, SVN Platforms: OS/400, IBM i, AS400, IBM Power Systems Infor & JDE Integration: Experience integrating IBM i / AS400 systems with Infor (LN, M3) and JD Edwards (JDE)—supporting data migration, interface development, batch jobs, APIs, and EDI‑driven business workflows. Domains- Banking | Retail | Manufacturing | Insurance | Healthcare | Life Sciences | E‑Commerce | Defense If your IBM i / AS400 or Mainframe environment is critical to revenue, let’s modernize it strategically, with stability and measurable ROI. Click “Hire Me” or send an invite to discuss your project. Keywords IBM i Modernization | AS400 Modernization | RPG Modernization | RPG Free | RPGLE | COBOL Modernization | NetCOBOL | Fujitsu COBOL | Mainframe Modernization | Green Screen Modernization | IBM i Web Enablement | RPG to Java | RPG to .NET | DB2 Migration | ERP Integration | Manhattan WMS | EDI Integration | AI Legacy Modernization | IBM Power Systems | API Integration | Legacy System Transformation |

  • IBM AS/400 Control Language
  • IBM RPG
  • RPG Development
  • IBM Db2
  • Migration
  • Green Screen
  • Visual LANSA
  • Mainframe
  • COBOL
  • Virtual Storage Access Method
  • Job Control Language
  • Customer Information Control System
  • Mulesoft
  • Electronic Data Interchange
  • PHP
  • IBM Power Systems
  • Infor F9
  • Oracle JD Edwards EnterpriseOne
  • MySQL
  • Artificial Intelligence
Zeeshan A.

Lahore, Pakistan

$50/hr
5.0
18 jobs

Your data infrastructure should be a competitive advantage — not a bottleneck. I design and build enterprise-grade cloud data platforms on Microsoft Azure that reduce pipeline costs, accelerate reporting, and give leadership teams the data confidence they need to make fast, accurate decisions. 📌 𝗪𝗵𝗼 𝗜 𝘄𝗼𝗿𝗸 𝘄𝗶𝘁𝗵: CTOs and Data Leaders at Series A–D startups and mid-market enterprises (100–2,000 employees) who are scaling their Azure data stack, migrating legacy warehouses to modern Lakehouse architectures, or building real-time analytics pipelines that actually ship. 📌 𝗪𝗵𝗮𝘁 𝗜 𝗱𝗲𝗹𝗶𝘃𝗲𝗿: • End-to-end Microsoft Fabric implementations (Lakehouse, Warehouse, Pipelines, Semantic Models) • Azure Data Factory & Azure Synapse pipeline architecture and optimization • Databricks Lakehouse builds on Delta Lake with PySpark & Unity Catalog • ETL/ELT pipeline design, migration, and production monitoring • Azure Data Lake Storage (ADLS Gen2) architecture and governance • Data Warehouse modernization (on-prem SQL → Azure Synapse / Fabric) • Power BI semantic layer and enterprise reporting 📌 𝗪𝗵𝘆 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝗰𝗵𝗼𝗼𝘀𝗲 𝗺𝗲: • Top Rated Plus — awarded to fewer than 3% of Upwork freelancers • 100% Job Success Score across 16 enterprise engagements • 8,400+ hours billed — one of the most experienced Azure data professionals on the platform • Azure Certified Data Engineer — not just self-declared expertise • Microsoft Fabric early adopter — hands-on since GA launch with production deployments 📌 𝗦𝗮𝗺𝗽𝗹𝗲 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀 𝗳𝗿𝗼𝗺 𝗽𝗮𝘀𝘁 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁𝘀: • Migrated legacy SQL Server DWH to Azure Synapse, reducing query time by 60% for a 500-employee retail group • Built Databricks Lakehouse pipeline processing 50M+ daily events with sub-2-hour SLA • Delivered full Microsoft Fabric implementation (Lakehouse + Power BI) for a financial services client in 8 weeks • Designed an ADF-based ETL framework, reducing pipeline maintenance overhead by 70% 📌 𝗧𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸: Microsoft Fabric · Azure Data Factory · Azure Synapse Analytics · Databricks · PySpark · Delta Lake · ADLS Gen2 · Azure Data Lake · Power BI · SQL · Python · ETL/ELT · Data Warehouse · Lakehouse Architecture · API Development · C# / .NET 📌 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗺𝗼𝗱𝗲𝗹: I work on hourly retainer engagements and fixed-price architecture projects. I don't take on more than 2 clients at a time, so my attention to your project is undivided. Most engagements begin with a paid 30-minute architecture discovery call. If your team is building on Azure and needs a senior data architect who delivers production-ready solutions — not prototypes — let's talk. Send me a message with your stack and what you're trying to achieve.

  • Data Engineering
  • ETL Pipeline
  • Databricks Platform
  • Data Warehousing & ETL Software
  • Data Migration
  • Azure Cosmos DB
  • API Development
  • PySpark
  • Azure Cognitive Services
  • .NET Core
  • Database Integration
  • Big Data
  • AWS Glue
  • Microsoft Azure SQL Database
  • Data Lake
  • C#
  • Python
Muhammad H.

Karachi, Pakistan

$10/hr
5.0
1 jobs

Slow pipelines, unreliable data, or a warehouse that breaks every time the source changes? I build data systems that don't. I'm a 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗙𝗮𝗯𝗿𝗶𝗰 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 with 5 years of experience delivering end-to-end data engineering and BI solutions. I currently work at Pakistan's largest payment gateway — a high-volume fintech environment where 𝗧𝗕-𝘀𝗰𝗮𝗹𝗲 𝘁𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗮𝘁𝗮, strict governance, and zero tolerance for pipeline failures are the daily reality. My specialty is building systems that are 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝗲𝗱 𝗽𝗿𝗼𝗽𝗲𝗿𝗹𝘆 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝘀𝘁𝗮𝗿𝘁 — metadata-driven, layered, monitored, and built to scale. 𝗪𝗛𝗔𝗧 𝗜 𝗕𝗨𝗜𝗟𝗗 ✦ 𝗠𝗲𝘁𝗮𝗱𝗮𝘁𝗮-𝗗𝗿𝗶𝘃𝗲𝗻 𝗘𝗧𝗟/𝗘𝗟𝗧 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 Control logic lives in configuration, not hardcoded. One framework handles dozens of sources with built-in logging, error handling, and restartability. Proven: reduced ETL runtime by 𝟯𝟴% on a production enterprise warehouse by eliminating redundant mapping layers. ✦ 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗲 𝗗𝗲𝘀𝗶𝗴𝗻 End-to-end warehouse design across 𝗦𝘁𝗮𝗴𝗶𝗻𝗴 → 𝗖𝗼𝗿𝗲 → 𝗚𝗼𝗹𝗱 (Medallion Architecture), with star/snowflake schema modeling, incremental loading, duplicate handling, and structured audit logging baked in. ✦ 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 Lakehouse and Warehouse design on OneLake, Fabric Data Factory pipelines, semantic models with 𝗥𝗼𝘄-𝗟𝗲𝘃𝗲𝗹 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 (𝗥𝗟𝗦), and report publishing as Fabric Apps for internal teams and external stakeholders. ✦ 𝗔𝘇𝘂𝗿𝗲 & 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 ADF-orchestrated cloud pipelines and PySpark-based distributed data processing on Databricks for large-scale, partitioned datasets. ✦ 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 & 𝗦𝗦𝗥𝗦 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 Semantic model design, DAX measures, drill-through dashboards, RLS enforcement, SSRS and Report Builder reports, and Fabric App deployment for enterprise stakeholders. ✦ 𝗟𝗲𝗴𝗮𝗰𝘆 𝗠𝗜𝗦 𝗠𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻 Migrated 20+ reports from legacy systems into a centralized, modern BI architecture without disrupting ongoing operations. 𝗥𝗘𝗖𝗘𝗡𝗧 𝗥𝗘𝗦𝗨𝗟𝗧𝗦 • Reduced ETL runtime by 𝟯𝟴% (4 hrs → 2.5 hrs) by optimizing metadata-driven SSIS pipelines • Built automated SFTP ingestion pipelines with archive logic to ensure 𝗶𝗻𝗰𝗿𝗲𝗺𝗲𝗻𝘁𝗮𝗹, 𝗱𝘂𝗽𝗹𝗶𝗰𝗮𝘁𝗲-𝗳𝗿𝗲𝗲 data loading • Delivered 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗲𝘀 supporting different business products across fintech, billing, and payments • Published 𝟭𝟱+ 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗿𝗲𝗽𝗼𝗿𝘁𝘀 as Fabric Apps with Row-Level Security for external stakeholders • Onboarded 10+ new source tables into a redesigned data warehouse while improving ETL performance and storage efficiency • Worked extensively with 𝗧𝗕-𝘀𝗰𝗮𝗹𝗲 𝘁𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗮𝘁𝗮 in a high-volume payment processing environment. 𝗖𝗢𝗥𝗘 𝗦𝗧𝗔𝗖𝗞 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰 | 𝗔𝘇𝘂𝗿𝗲 𝗗𝗮𝘁𝗮 𝗙𝗮𝗰𝘁𝗼𝗿𝘆 | 𝗔𝘇𝘂𝗿𝗲 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀 | 𝗣𝘆𝗦𝗽𝗮𝗿𝗸 | 𝗔𝗽𝗮𝗰𝗵𝗲 𝗦𝗽𝗮𝗿𝗸 | 𝗦𝗦𝗜𝗦 | 𝗦𝗤𝗟 𝗦𝗲𝗿𝘃𝗲𝗿 | 𝗢𝗿𝗮𝗰𝗹𝗲 | 𝗣𝗼𝘀𝘁𝗴𝗿𝗲𝗦𝗤𝗟 | 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 | 𝗦𝗦𝗥𝗦 | 𝗧-𝗦𝗤𝗟 | 𝗣𝗟/𝗦𝗤𝗟 | 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴 | 𝗠𝗲𝗱𝗮𝗹𝗹𝗶𝗼𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 | 𝗦𝘁𝗮𝗿 𝗦𝗰𝗵𝗲𝗺𝗮 | 𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲 𝗦𝗰𝗵𝗲𝗺𝗮 | 𝗘𝗧𝗟/𝗘𝗟𝗧 | 𝗟𝗮𝗸𝗲𝗵𝗼𝘂𝘀𝗲 𝗕𝗘𝗦𝗧-𝗙𝗜𝗧 𝗣𝗥𝗢𝗝𝗘𝗖𝗧𝗦 • Data warehouse or lakehouse design from scratch • ETL/ELT pipeline build, optimization, or troubleshooting • Microsoft Fabric or Azure migration from legacy on-prem systems • Power BI, SSRS, or Fabric App reporting solutions • SQL performance tuning, stored procedures, and indexing • Production pipeline monitoring, job scheduling, and failure resolution 𝗛𝗢𝗪 𝗜 𝗪𝗢𝗥𝗞 I understand your business process, data sources, and reporting needs first. Then I design a practical architecture, build clean and observable pipelines, validate the data, and deliver reporting-ready models your team can actually trust — with 𝗹𝗼𝗴𝗴𝗶𝗻𝗴, 𝗲𝗿𝗿𝗼𝗿 𝗵𝗮𝗻𝗱𝗹𝗶𝗻𝗴, and 𝗷𝗼𝗯 𝘀𝗰𝗵𝗲𝗱𝘂𝗹𝗶𝗻𝗴 built in from day one, not added as an afterthought. 📩 𝗦𝗲𝗻𝗱 𝗺𝗲 𝗮 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 𝘄𝗶𝘁𝗵 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗱𝗲𝘁𝗮𝗶𝗹𝘀 — 𝗜 𝗿𝗲𝘀𝗽𝗼𝗻𝗱 𝗾𝘂𝗶𝗰𝗸𝗹𝘆 𝗮𝗻𝗱 𝘄𝗶𝗹𝗹 𝗼𝘂𝘁𝗹𝗶𝗻𝗲 𝗮 𝗰𝗹𝗲𝗮𝗿 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁.

  • Data Engineering
  • ETL Pipeline
  • Microsoft Azure
  • Microsoft Power BI
  • Databricks Platform
  • Data Warehousing
  • Data Lake
  • SQL
  • Data Modeling
  • SQL Server Integration Services
  • SQL Server Reporting Services
  • Microsoft SQL Server
  • Oracle
  • Fabric
  • Database Development
  • PySpark
  • Business Intelligence
  • PostgreSQL
  • Microsoft Power BI Data Visualization
  • Big Data

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What does an IBM InfoSphere DataStage specialist do?

An IBM InfoSphere DataStage specialist designs and builds extract, transform, and load jobs that move data from source systems to target databases. This developer uses the InfoSphere DataStage and QualityStage Designer client to construct parallel job designs that process large volumes of information efficiently. The work centers on creating reusable components and configuring job executions within the InfoSphere DataStage Repository. These specialists structure job logic as sequential designs that execute as parallel processes to handle complex data integration tasks.

  • Designs InfoSphere DataStage jobs to move data from specified sources to specified targets using the Designer client. The specialist maps source fields to target fields and defines the flow of data through various processing stages. This work ensures that raw data from disparate systems arrives in a structured format ready for analysis or storage. The developer selects appropriate stages to handle specific data types and transformation requirements.
  • Builds transformations within jobs using stages such as the Transformer stage to modify data values and structures. The specialist writes logic to clean, validate, and convert data formats during the extraction process. This step involves implementing business rules directly into the job design to maintain data quality. The developer tests these transformations to confirm they produce the expected output for downstream systems.
  • Develops parallel job designs and reusable components like shared containers stored in the Repository for future use. The specialist creates modular job parts that other developers can incorporate into their own designs. This approach reduces development time and maintains consistency across multiple data integration projects. The developer manages these assets within the InfoSphere DataStage Repository to ensure version control and easy access.
  • Schedules and runs DataStage server jobs, including parallel job invocations, using built-in job scheduling features. The specialist configures execution parameters so jobs run at specific times or in response to triggers. This work involves monitoring job performance and adjusting configurations to optimize processing speed. The developer ensures that jobs complete successfully and handles any errors that arise during execution.
  • Creates and maintains job assets such as shared containers that store common logic for reuse across projects. The specialist updates these containers when business rules change to keep all dependent jobs current. This maintenance task requires careful testing to avoid breaking existing job flows. The developer documents changes to help team members understand how shared components function.

How to hire an IBM InfoSphere DataStage specialist on Upwork

Step 1: Post a job

Define your data integration needs clearly to attract qualified candidates. Use the Job Post Generator powered by Uma™, Upwork's Mindful AI to draft a precise description. 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 one.

  • Specify that the freelancer must design InfoSphere DataStage jobs using the Designer client to move data from sources to targets.
  • List required experience with building transformations using stages such as the Transformer stage within parallel job designs.
  • Request examples of reusable components or shared containers stored in the InfoSphere DataStage Repository for efficient development.

Step 2: Evaluate candidates

Look for portfolios that demonstrate concrete ETL development work. Uma can run instant video interviews and build shortlists with side-by-side comparisons to help you assess technical fit quickly.

  • Verify the candidate has authored parallel job designs that execute job stages as distinct processes or instances.
  • Check for evidence of configuring and triggering job execution using native job scheduling features in InfoSphere DataStage.
  • Confirm the freelancer has created server jobs and managed parallel job invocations for different datasets.

Step 3: Interview your top choices

Discuss specific technical approaches to data movement and transformation. Schedule and conduct interviews within Upwork Messages to receive an immediate transcript and summary after each session.

  • Ask how they structure job logic as sequential designs that execute as parallel processes for performance.
  • Inquire about their method for reusing job parts via containers stored in the Repository across multiple projects.
  • Discuss how they handle running jobs that require multiple invocations with different parameters for varied datasets.

Step 4: Agree on scope and begin work

Set clear deliverables and milestones for your data integration project. Use Upwork Messages and the contract workroom for communication and project management while relying on identity verification, payment protection, hourly tracking, and project funds for security.

  • Define the specific DataStage jobs needed to move data from your specified sources to your target systems.
  • Outline the data transformation logic that must be implemented using specific DataStage stages like the Transformer.
  • Establish requirements for configured job executions including server or parallel job invocations and scheduling setups.

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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 an IBM InfoSphere DataStage specialist cost?

Hiring an IBM InfoSphere DataStage specialist typically costs $500-$1,500 per project, depending on scope and experience. Final pricing depends on the complexity of data transformations, the number of source systems, required parallel processing configurations, and the freelancer's experience level.

Job design assessment

$500-$1,000/project

Entry-level to mid-level
  • Review of existing job designs and performance bottlenecks
  • Recommended changes for parallel processing efficiency
  • Updated notes on job logic and dependencies

ETL job development

$1,000-$2,500/project

Mid-level
  • Built jobs that move data from sources to targets
  • Configured Transformer stages for data cleansing
  • Validation logs confirming accurate data movement

Reusable component creation

$2,500-$4,500/project

Mid-level to senior-level
  • Developed reusable job parts stored in the Repository
  • Instructions for incorporating containers into new jobs
  • Organized assets within the InfoSphere DataStage Repository

Parallel job configuration

$4,500-$7,000/project

Senior-level
  • Structured job logic to execute as parallel processes
  • Configured job invocations with parameter handling
  • Logs showing improved execution speed and resource use

Enterprise data pipeline

$7,000-$12,000/project

Expert-level
  • Complete system moving data across multiple platforms
  • Robust mechanisms for failed job invocations and retries
  • Exported jobs and containers for production environment

Frequently asked questions

Is hiring an IBM InfoSphere DataStage specialist worth it?

For most businesses, yes: hiring an IBM InfoSphere DataStage specialist is worthwhile. These specialists design jobs that move and transform data from sources to targets using the Designer client. They build parallel job designs and reusable components stored in the Repository. This work supports complex data integration needs that general developers may not handle.

How do I evaluate IBM InfoSphere DataStage specialist candidates?

Look for candidates who demonstrate experience with the InfoSphere DataStage and QualityStage Designer client. Ask them to describe how they structure job logic as sequential designs that execute as parallel processes. A strong candidate explains how they use stages like the Transformer stage to implement transformation logic. Request examples of shared containers they created for reuse in other job designs.

What tasks does an IBM InfoSphere DataStage specialist perform?

An IBM InfoSphere DataStage specialist designs jobs to move data from specified sources to specified targets. They configure and trigger job execution using scheduling features and run server or parallel jobs.

Which tools does an IBM InfoSphere DataStage specialist use?

These specialists use the InfoSphere DataStage and QualityStage Designer client to develop job designs. They also manage assets in the InfoSphere DataStage Repository and configure job scheduling features.