Senior Data Engineer

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.

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