Hire the Best Big Data Engineers in Texas

𝐈 𝐛𝐮𝐢𝐥𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐠𝐫𝐚𝐝𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 𝐟𝐨𝐫 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐝𝐞𝐚𝐥𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐛𝐫𝐨𝐤𝐞𝐧 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, 𝐬𝐜𝐚𝐭𝐭𝐞𝐫𝐞𝐝 𝐬𝐲𝐬𝐭𝐞𝐦𝐬, 𝐬𝐥𝐨𝐰 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐮𝐧𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞 𝐦𝐞𝐭𝐫𝐢𝐜𝐬. I’m a Senior Data Engineer with 10+ years of experience building cloud data platforms, ETL/ELT pipelines, lakehouses, warehouses, and analytics-ready data layers using Microsoft Fabric, Snowflake, AWS, BigQuery, dbt, Python, SQL, Airflow, Fivetran, Airbyte, and Databricks. My focus is not just moving data from point A to point B. I design reliable data systems that are automated, scalable, well-modeled, and trusted by business teams. 𝐖𝐡𝐚𝐭 𝐈 𝐡𝐞𝐥𝐩 𝐰𝐢𝐭𝐡 ✅ 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐚𝐛𝐫𝐢𝐜 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Lakehouse, Warehouse, Dataflows Gen2, pipelines, notebooks, semantic models, Medallion architecture, and Power BI-ready data layers. ✅ 𝐂𝐥𝐨𝐮𝐝 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, SQL Server, and Azure Synapse architecture. ✅ 𝐄𝐓𝐋/𝐄𝐋𝐓 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 API ingestion, database replication, SaaS integrations, file ingestion, batch jobs, incremental loads, and scheduled workflows. ✅ 𝐝𝐛𝐭 & 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Staging, intermediate, marts, incremental models, tests, documentation, metric definitions, and business logic standardization. ✅ 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 & 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 Airflow, Dagster, AWS Lambda, Glue, Step Functions, ADF, CI/CD, monitoring, retries, alerts, and production workflow automation. ✅ 𝐃𝐚𝐭𝐚 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 & 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 Deduplication, reconciliation, schema drift handling, validation rules, MDM, Golden Record logic, RBAC, access control, and audit-ready reporting layers. 𝐑𝐞𝐜𝐞𝐧𝐭 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐚𝐛𝐫𝐢𝐜 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 Built a centralized Fabric platform with Lakehouse, Warehouse, Dataflows, pipelines, semantic models, and Power BI reporting layers for a global organization with fragmented reporting sources. 𝐍𝐞𝐚𝐫 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 Designed operational pipelines into Snowflake with incremental ingestion, schema change handling, deduplication, retries, and reliable dbt-based reporting models. 𝐌𝐨𝐝𝐞𝐫𝐧 𝐒𝐚𝐚𝐒 𝐝𝐚𝐭𝐚 𝐬𝐭𝐚𝐜𝐤 Centralized HubSpot, Stripe, GA4, Google Ads, Salesforce, MongoDB, and product data into BigQuery/Snowflake using Fivetran, Airbyte, dbt, Dagster, and Metabase. 𝐋𝐞𝐠𝐚𝐜𝐲 𝐦𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐜𝐥𝐨𝐮𝐝 𝐰𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 Led migrations from SQL Server, SAP BW, Oracle, Hadoop, and on-prem systems into modern cloud warehouses with optimized performance and automated workflows. 𝐀𝐖𝐒 𝐝𝐚𝐭𝐚 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 Built automated workflows using S3, Lambda, Glue, Step Functions, IAM, SNS, CloudWatch, and Python to reduce manual reporting and improve pipeline reliability. 𝐓𝐨𝐨𝐥𝐬 𝐈 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 Microsoft Fabric, Snowflake, BigQuery, Redshift, Databricks, Azure Synapse, PostgreSQL, SQL Server, Oracle, SAP BW, Hadoop, dbt, Python, SQL, Airflow, Dagster, Fivetran, Airbyte, ADF, SSIS, Talend, AWS S3, Lambda, Glue, Step Functions, IAM, SNS, CloudWatch, Power BI, Tableau, Metabase, and Looker. You should reach out if you need a senior data engineer to: ✅ Build a cloud data warehouse or lakehouse ✅ Migrate legacy systems to Snowflake, Fabric, BigQuery, or AWS ✅ Fix unreliable ETL/ELT pipelines ✅ Design dbt models and trusted reporting layers ✅ Automate manual reporting workflows ✅ Integrate APIs, CRMs, ERPs, databases, and SaaS platforms ✅ Build production-ready data infrastructure for analytics and BI If your data stack is messy, slow, or hard to trust, send me a message. I’ll help you map the cleanest path from scattered systems to a reliable data platform.

𝗜 𝗱𝗲𝘀𝗶𝗴𝗻 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝗱𝗮𝘁𝗮 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝘂𝗻𝗶𝗳𝘆 𝗳𝗿𝗮𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗶𝗻𝘁𝗼 𝗿𝗲𝗹𝗶𝗮𝗯𝗹𝗲, 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗴𝗿𝗮𝗱𝗲 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲. Whether you are battling 12-hour query runtimes, migrating legacy silos, or building an AI-ready data lakehouse, I provide the architectural strategy and engineering rigor required to scale. With 20+ years of experience delivering high-stakes production systems for global brands like Apple, Overstock, and Medline, I move beyond task-based support to own your technical roadmap. As the Managing Director of ADLAB Solutions, I lead a vetted engineering bench capable of scaling delivery across Data Engineering, AI/ML, and UI/UX—ensuring your stack remains a growth driver, not a bottleneck. ──────────────────────────── 📊 THE IMPACT (By the Numbers) • 1B+ Rows modeled cleanly with 99.9% pipeline uptime. • 35% Avg. Reduction in Snowflake/Cloud compute costs through refactoring. • 150+ Dashboards delivered with 70% latency improvement. • 30+ Hours/Week saved per client through metadata-driven automation. ──────────────────────────── 🛠️ ARCHITECTURAL FOCUS AREAS • Warehouse Modernization & Migrations: Specialized in Teradata/SQL Server → Snowflake, BigQuery, or Fabric. I focus on zero-downtime cutovers and "Set-Based" design to maximize cloud-native performance. • Metadata-Driven ELT/ETL Pipelines: Building idempotent, self-healing pipelines (dbt, Airflow, Matillion, ADF). I design systems that handle schema drift automatically to protect downstream AI and BI models. • AI & Agentic Data Foundations: Architecting semantic layers for Snowflake Cortex, RAG-powered knowledge assistants, and predictive "Nowcasting" systems that combine high-frequency signals with broad benchmarks. • Analytics Engineering & BI Governance: Shipping governed Power BI, Tableau, and Sigma environments. I fix the "Broken Trust" in numbers by implementing Row-Level Security (RLS) and centralized metrics definitions. • Real-Time & Managed Services: CDC patterns for sub-minute freshness (Kafka, GoldenGate) and ongoing SLA-based infrastructure monitoring and administration. ──────────────────────────── 🎯 TRUSTED BY Apple • Teradata • Medline • Overstock • Bed Bath & Beyond • Salt Lake Bees • Poppi • Utah Jazz ──────────────────────────── ✅ THE ADLAB ADVANTAGE • Enterprise Governance: Experienced with remote workstations (VDI), M365/Google security protocols, and HIPAA/regulated environments. • Strategic Roadmap: I identify technical debt and map a cost-efficient architecture. • Managed Delivery: My team executes the build with senior-level oversight. 𝗜𝗳 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 𝘀𝘁𝗮𝗰𝗸 𝗶𝘀 𝗳𝗮𝗶𝗹𝗶𝗻𝗴 (𝘂𝗻𝗿𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗿𝗲𝗽𝗼𝗿𝘁𝘀, 𝘀𝘁𝘂𝗰𝗸 𝗺𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀, 𝗼𝗿 𝗿𝘂𝗻𝗮𝘄𝗮𝘆 𝗰𝗹𝗼𝘂𝗱 𝗰𝗼𝘀𝘁𝘀), 𝘀𝗲𝗻𝗱 𝗺𝗲 𝘁𝗵𝗲 𝗱𝗲𝘁𝗮𝗶𝗹𝘀. 𝗜’𝗹𝗹 𝗽𝗿𝗼𝘃𝗶𝗱𝗲 𝗮 𝗯𝗿𝗶𝗲𝗳 𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗮𝗻𝗱 𝘁𝗲𝗹𝗹 𝘆𝗼𝘂 𝗲𝘅𝗮𝗰𝘁𝗹𝘆 𝗵𝗼𝘄 𝘄𝗲’𝗹𝗹 𝗳𝗶𝘅 𝗶𝘁.

🏆 Achieved Top-Rated Freelancer status (Top 10%) with a proven track record of success. Past experience: Twitter, Spotify, & PwC. I am a certified data engineer & software developer with 5+ years of experience. I am familiar with almost all major tech stacks on data science/engineering and app development. If you require support in your projects, please do get in touch. Programming Languages: Python | Java | Scala | C++ | Rust | SQL | Bash Big Data: Airflow | Hadoop | MapReduce | Hive | Spark | Iceberg | Presto | Trino | Scio | Databricks Cloud: GCP | AWS | Azure | Cloudera Backend: Spring Boot | FastAPI | Flask AI/ML: Pytorch | ChatGPT | Kubeflow | Onnx | Spacy | Vertex AI Streaming: Apache Beam | Apache Flink | Apache Kafka | Spark Streaming SQL Databases: MSSQL | Postgres | MySql | BigQuery | Snowflake | Redshift | Teradata NoSQL Databases: Bigtable | Cassandra | HBase | MongoDB | Elasticsearch Devops: Terraform | Docker | Git | Kubernetes | Linux | Github Actions | Jenkins | Gitlab

With over 15 years in applied engineering, I specialize in AI/ML, computer vision, cloud migration, and data platforms. I help teams deliver measurable results with practical, production-ready solutions. AI/ML Engineering & GenAI: Supervised/unsupervised modeling, LLM/RAG apps with grounded citations, prompt/eval/guardrails, and task automation. Experience fine-tuning, distillation, and benchmarking so models are accurate and cost-effective. Computer Vision: Object detection/segmentation (YOLO/RT-DETR), pose estimation (MoveNet/RTMPose/MediaPipe), action recognition, OCR/receipt parsing, and video analytics. End-to-end dataset work (collection, labeling, Roboflow), augmentation, and on-device/edge export (Core ML/TFLite) when needed. MLOps & Deployment: Reproducible training, experiment tracking, registries, CI/CD for models, scalable inference (FastAPI/Triton), and monitoring/drift alerts across AWS/GCP/Azure. Cloud Migration & Data Engineering: Lift-and-shift and re-platforming to AWS/GCP/Azure with minimal downtime; ELT/ETL pipelines, lakehouse stacks, and analytical models in Snowflake/BigQuery/Databricks. Dashboards and KPI reporting that tie directly to business goals. SAP ERP & Enterprise Integration: Implementation and customization to streamline processes, with data pipelines that connect SAP to analytics and AI use cases. I’m pragmatic, detail-oriented, and focused on client outcomes—clear communication, small milestones, and results you can measure. Let’s discuss your goals and map the fastest path to value.

Looking for a seasoned operator to help your business solve its data problems? I can help! With 7+ years in the data world, I've worked with clients large and small across the full data stack. My services: * Data collection * Data warehousing * Data visualization