Posted:4 hours ago|
Platform:
Work from Office
Full Time
We seek a Data Engineer (Mid-level) with 4-6 years of hands-on experience in designing, building, and optimizing data pipelines. You will work closely with AI/ML teams to ensure data availability, quality, and performance for analytics and GenAI use cases.Key
Responsibilities
1. Data Pipeline DevelopmentBuild and maintain scalable ETL/ELT pipelines for structured and unstructured data.Ingest data from diverse sources (APIs, streaming, batch systems).2. Data Modeling & WarehousingDesign efficient data models to support analytics and AI workloads.Develop and optimize data warehouses/lakes using Redshift, BigQuery, Snowflake, or Delta Lake.3. Big Data & StreamingWork with distributed systems like Apache Spark, Kafka, or Flink for real-time/large-scale data processing.Manage feature stores for ML pipelines.4. Collaboration & Best PracticesWork closely with Data Scientists and ML Engineers to ensure high-quality training data.Implement data quality checks, observability, and governance frameworks.
o Programming: Python/Scala/Java (Python preferred).
o Big Data & Processing: Apache Spark, Kafka, Hadoop.o Databases: SQL/NoSQL (Postgres, MongoDB, Cassandra).o Data Warehousing: Snowflake, Redshift, BigQuery, or similar.o Orchestration: Airflow, Luigi, or similar.o Cloud Platforms: AWS, Azure, or GCP (data services).o Version Control & CI/CD: Git, Jenkins, GitHub Actions.o MLOps/GenAI pipelines (feature engineering, embeddings, vector DBs).
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