JUNIOR DATA ENGINEER —
- 1–3 years of hands-on experience with PySpark (DataFrames, Spark SQL basics) — production or solid academic/project experience acceptable.
- Working knowledge of Fivetran or a similar ELT tool (Airbyte, Stitch) — setting up connectors, monitoring syncs.
- Solid SQL fundamentals and exposure to a cloud data warehouse (Snowflake / Redshift / BigQuery).
- Basic Python scripting ability for data tasks.
- Exposure to at least one cloud platform (AWS / Azure / GCP), internship or project-level acceptable.
- Eager to learn, works well under guidance from senior engineers; not expected to design architecture independently.

SENIOR DATA ENGINEER — REQUIREMENTS
- 5+ years of hands-on experience with PySpark (DataFrames, Spark SQL, RDDs, performance tuning, job optimization) in production.
- 3+ years configuring and managing Fivetran connectors at scale (custom connectors, schema drift handling, sync orchestration, troubleshooting).




- Strong SQL and proven data modeling / warehouse design experience (Snowflake / Redshift / BigQuery).
- Deep experience with at least one major cloud platform (AWS, Azure, or GCP), including cost and performance optimization.
- Proven ability to design end-to-end pipeline architecture and lead technical decisions.
- Experience mentoring junior engineers and reviewing code/pipeline designs.

RESPONSIBILITIES
- Design, build, and optimize PySpark ETL/ELT pipelines for large-scale batch and/or streaming data.
- Own Fivetran connector strategy across [X] source systems, including custom connector development.
- Define data architecture and standards; review junior engineers' pipeline designs.
- Collaborate with analytics/BI teams and business stakeholders to define data requirements.
- Implement data quality frameworks, validation, and monitoring across pipelines.

📌 Data Engineer (Pune)
🏢 Sonata Software
📍 Pune