Senior Data Engineer

Experience Job Summary for Senior Data Engineer (List Format): 6–9 years of relevant experience in data engineering or related roles.

Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines for structured and semi-structured data.

Build robust data ingestion frameworks from APIs, databases, SaaS platforms, logs, and telemetry systems.

Develop and optimize data warehouses and data lakes for high performance and scalability.

Implement data transformation, aggregation, and business logic based on business requirements.

Ensure data quality, validation, reconciliation, and consistency across systems.

Monitor data pipelines for performance, failures, and data freshness; implement alerting and observability.

Collaborate with data analysts, data scientists, and product teams to deliver high-quality datasets.

Implement security, access control, and compliance best practices for data platforms.

Document data models, pipelines, and operational processes for maintainability and governance.

Support downstream use cases such as BI dashboards, reporting, billing systems, and machine learning pipelines.

Continuously improve data engineering practices, performance, and reliability.

Participate in architecture discussions and help define scalable data platform strategies.

Required Skills Strong programming skills in Python and SQL.

Hands-on experience with ETL/ELT frameworks (e.g., Airflow, dbt, Spark).

Expertise in relational databases and modern data warehouses.

Strong understanding of data modelling (star/snowflake schemas), indexing, and query optimization.

Experience building batch and/or streaming data pipelines.

Experience with cloud platforms (AWS, Azure, or GCP).

Proficiency with object storage systems (S3, GCS, ADLS).

Experience with data formats such as Parquet, Avro, and JSON.

Familiarity with APIs and data integration patterns. Preferred/Additional Skills Experience with real-time or telemetry data pipelines.

Exposure to data reconciliation, billing systems, or financial datasets.

Experience with data platforms such as Snowflake, BigQuery, Redshift, Incorta.

Knowledge of CI/CD pipelines for data engineering workflows.

Understanding of data governance, lineage, and metadata management.

Experience supporting high-scale or enterprise-grade systems.

Familiarity with distributed data processing and performance tuning.

Additional Qualifications

Proven experience in designing and implementing scalable data pipelines and platforms.

Strong problem-solving and analytical skills.

Experience in cross-functional, agile teams.

Excellent communication and documentation skills.

Work Details Hybrid work model: Minimum 2 days in office (Tuesday and Thursday); additional days as needed.

Location: Pune, Maharashtra, India.

Normal business hours with flexibility for cross-time-zone collaboration.