SENIOR DATA ENGINEER

• 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

Senior:

• 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.

NICE-TO-HAVE SKILLS (EITHER LEVEL)

• Experience with Databricks and Delta Lake.
• Familiarity with orchestration tools (Airflow, Databricks Workflows).
• dbt experience for transformation/modeling.
• Exposure to streaming technologies (Kafka, Spark Structured Streaming).
• Relevant certifications (Databricks Certified Data Engineer, Fivetran certification, cloud data engineer certs).
• Prior experience in [specific industry, e.g., healthcare, finance, retail], if relevant.