Data Engineer

Job Title Data Engineer Location Dallas, TX; Oklahoma City, OK; Little Rock, AR; Shreveport, LA; Albuquerque, NM Employment Type W2, not C2C Key Responsibilities Lead design, development and optimization of large‑scale, secure and high‑performance data pipelines across batch, real‑time and event‑driven systems. Partner with cross‑functional teams to deliver analytics, reporting and ML‑ready datasets. Architect, build and optimise batch and real‑time data pipelines for enterprise‑scale systems. Integrate datasets from databases, files, APIs and event streams (Kafka/Kinesis). Ensure data quality, scalability, reliability and performance across pipelines. Prepare curated datasets for analytics, reporting and ML models. Implement data security (access control, encryption, masking) and governance practices. Monitor, troubleshoot and tune data infrastructure for optimal efficiency. Collaborate closely with data scientists, architects and business teams to define data solutions. Introduce best practices, mentor engineers and drive data engineering standards. Mandatory Skills (Experience) Data Engineering: 8-12 years Python / Java / Spark: 6-10 years (strong coding) SQL & NoSQL Databases: 6-10 years (RDS, Redshift, DynamoDB, Synapse, BigQuery, MongoDB) Batch & Streaming Systems: 5-8 years (Kafka/Kinesis/event‑driven systems) Cloud Experience: 5-8 years across AWS, Azure, Google Cloud Platform (minimum two clouds) APIs & Messaging Systems: 4-6 years (REST, event‑driven architectures) Large‑scale Dataset Engineering: 5-8 years (performance optimisation) Graph Databases: 1-2 years (Neptune, RDF4j) Vector Databases: 1-2 years (Pinecone, FAISS) Data Security: 3-5 years (encryption, access control, masking) Soft Skills Strong problem‑solving & analytical thinking Excellent communication across technical and business teams High ownership, adaptability and collaborative mindset Nice to Have Domain knowledge: Insurance, Banking, Mortgage Containers & CI/CD: Docker, Kubernetes Streaming tools: Kafka, Kinesis (advanced) Exposure to NLP and data segmentation Experience with data visualization tools Contact Tanuja P Phone: Email: #J-18808-Ljbffr Jobs via Dice