Role Overview
Linkedin is hiring a mid-level Data Engineer (Analyst). This is a full-time role in Anantapur. Part of Linkedin's Data Engineering hiring. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job Description
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, BigQuery, 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/BigQuery/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: CloudWatch, Azure Monitor, GCP Monitoring, Datadog
- CI/CD + Git-based workflows for data pipelines
Frequently Asked Questions
How do I apply for the Data Engineer (Analyst) position at Linkedin?
Use the Apply button above to submit your application directly to Linkedin. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Data Engineer (Analyst) position at Linkedin located?
This position is based in Anantapur. Linkedin has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Data Engineer (Analyst) at Linkedin earn?
Linkedin has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Data Engineer (Analyst) role at Linkedin posted?
This role was posted on April 6, 2026 (63 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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