Senior Data Engineer
Summary
Senior Data Engineer builds and maintains scalable data pipelines and infrastructure for analytics and ML using SQL, Python, and cloud platforms in a hybrid role based in Hyderabad or Pune.
Job Title: Senior Data Engineer
Exp: 6-12 Yrs
Notice Period: 0-30 days
Mode of Work: Hybrid
Work Location: Hyd/Pune
We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that support analytics, reporting, and machine learning initiatives. The ideal candidate has strong experience with SQL, Python, cloud platforms, and modern data engineering tools. You will collaborate with data analysts, data scientists, and software engineers to ensure reliable, high-quality data is available across the organization.
Job Description:
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Build and optimize data warehouses, data lakes, and data models.
- Integrate data from multiple sources, including APIs, databases, and third-party systems.
- Ensure data quality, consistency, security, and governance.
- Monitor and troubleshoot data pipelines and resolve performance issues.
- Optimize SQL queries and database performance.
- Collaborate with cross-functional teams to understand data requirements and deliver solutions.
Requirements
Core Data Engineering
& Architecture
- Design
and build end-to-end data pipelines (ETL/ELT) for structured and
unstructured data
- Develop
scalable data platforms handling terabytes of data with high reliability
and low latency
- Strong
expertise in data modeling, warehousing, and lakehouse architectures
- Own
data quality, lineage, governance, and observability frameworks
- Hands-on
experience with Spark, Hadoop, Kafka, Flink (batch + real-time processing)
- Build
and optimize high-throughput, distributed data systems
- Experience
in streaming + event-driven architectures for large-scale financial data
- Deep
expertise in AWS / Azure / GCP (Data Lakes, Warehouses, Compute, Storage)
- Tools:
Databricks, Snowflake, Redshift, Synapse, BigQuery
- Pipeline
orchestration using Airflow, Prefect, or similar frameworks
- Strong
coding in Python, SQL, Scala
- Focus
on performance optimization, reliability, and production-grade systems
- Experience
with CI/CD, DevOps, and infrastructure-as-code
- Ability
to design architectures and make technology decisions at scale
- Strong
understanding of:
- Trade
lifecycle, transactions, risk, compliance, regulatory reporting
- Customer
360, payments, lending, capital markets data and Wealth Management
Business
- GenAI
/ LLM integration (RAG, embeddings, vector stores)
- Lead
legacy-to-cloud data platform migrations
- Drive
data re-engineering, system decomposition, and modernization initiatives
- Drive
resilience, failover, and incident response frameworks
- Work
across engineering, data science, risk, compliance, and product teams
- Ability
to translate business needs (risk, reporting, revenue) into data solutions
- Mentor
engineers and drive engineering best practices and standards
Benefits
Standard Company Benefits