Data Engineer

Job Title: Data Engineer
Location: Dallas TX Oklahoma City Ok Little Rock AK Shreveport LI Albuquerque NM
Looking for W2 No C2C

Job Description:

• Lead the 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.

Key Responsibilities:

• Architect build and optimize 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 (with Experience):

• Data Engineering (Overall): 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 optimization)
• 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 & 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 usage)
• Exposure to NLP and data segmentation
• Experience with data visualization tools

Best Regards:

Tanuja P
Phone: 1-
Email: