Data Engineer

JD :-

Data Engineer (Mid-Level 06 to 12 years)

Cloud Environments -

Familiarity with major cloud platforms (AWS, GCP, Azure)

Data Architecture -

Experience with modern data architectures (data lakes, lakehouses, hubs)

Data Ingestion -

Proficiency in ingestion tools (Kafka, AWS Glue) and formats (Iceberg, Parquet)

Data Streaming -

Knowledge of streaming architectures and tools (Kafka, Flink)

Data Modeling -

Strong background in SQL-based frameworks and orchestration tools (dbt, Glue, Airflow). Experience with SCD and schema evolution

Data Transformation (Spark) -

Familiarity with Spark for transformation, streaming, tuning, debugging with Spark UI

Programming -

Proficient in Python, Java, Scala (or similar). Expert-level SQL

DevOps -

Demonstrated experience in DevOps practices (code management, CI/CD, deployment)

Data Governance -

Understanding of governance principles (quality, privacy, security)