Data Engineer

Data Pipeline Development:

·Build and maintain scalable ETL/ELT pipelines for structured and unstructured data

·Ingest data from diverse sources (APIs, streaming, batch systems).

Data Modeling & Warehousing

·Design efficient data models to support analytics and AI workloads.

·Develop and optimize data warehouses/lakes using Redshift, BigQuery, Snowflake, or Delta Lake.

Big Data & Streaming

·Work with distributed systems like Apache Spark, Kafka, or Flink for real-time/large-scale data processing.

·Manage feature stores for ML pipelines

Collaboration & Best Practices

·Work closely with Data Scientists and ML Engineers to ensure high-quality training data.

·Implement data quality checks, observability, and governance frameworks.