Job Description & How to Apply Below
Job Title:
Data Engineer (Analyst)
Experience:
2.5 to 5 Years
Location:
PAN India (Remote/On-site as applicable)
About the Role:
We are looking for Data Engineer (Analyst) to build and maintain reliable data pipelines and analytics-ready datasets that power BI reporting, product insights, and business decision-making. You’ll work across multiple data sources, model clean reporting layers, and ensure data quality end-to-end.
Key Responsibilities:
Build and maintain scalable ETL/ELT pipelines (batch and incremental) using SQL + Python
Integrate data from databases, APIs, SaaS tools, event data, and flat files
Design analytics-ready data models (star schema/marts) for self-serve reporting
Create and optimize transformations in a cloud warehouse/lakehouse (e.g., Snowflake, Big Query, Redshift, Synapse, Databricks )
Partner with stakeholders to define KPIs, metric logic, and reporting requirements
Maintain dashboards and reporting outputs in tools like Power BI, Tableau, Looker, or Sigma
Implement data quality checks , monitoring, alerts, and documentation to keep datasets trusted
Tune performance and cost (incremental loads, partitioning, query optimization, file formats)
Required Skills:
Strong SQL skills (CTEs, window functions, joins, aggregations, optimization)
Strong Python skills for transformations and automation
Hands-on experience with at least one cloud platform: AWS / Azure / GCP
Experience with a modern data warehouse/lakehouse (Snowflake/Big Query/Redshift/Synapse/Databricks)
Solid understanding of ETL/ELT patterns (incremental loads, retries, idempotency, basic CDC)
Comfort with data modeling for analytics and BI reporting
Experience building stakeholder-friendly reporting in a BI tool (Power BI/Tableau/Looker/Sigma)
Nice to have:
Orchestration tools: Airflow, dbt, Dagster, Prefect, ADF, Glue , etc.
Streaming/event data: Kafka, Kinesis, Pub/Sub
Monitoring/logging: Cloud Watch, Azure Monitor, GCP Monitoring, Datadog
CI/CD + Git-based workflows for data pipelines
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