Key Responsibilities
Build
scalable batch and streaming pipelines using Python, PySpark, and
SQL.
Develop
and maintain ETL/ELT workflows and data ingestion frameworks.
Design
dimensional data models (fact/dimension, star schema, 3NF).
Write
and optimize complex SQL transformations for large datasets.
Ensure
data quality, validation, lineage, and governance best practices.
Tune
Spark jobs and SQL queries for performance and cost.
Work
with AWS services (S3, Glue, EMR, Lambda, Step Functions).
Implement
CI/CD, testing, and production deployment of data workflows.
Monitor,
log, and troubleshoot data pipelines in production.
Participate
in architecture discussions and drive technical decisions.
Collaborate
with analytics, product, and data science teams.
Mentor
junior engineers and promote best practices.

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Required Skills Qualifications
5+
years of experience in data engineering or related roles.
Robust
Python development experience.
Advanced
SQL (analytical queries, performance tuning).
Expertise
in PySpark (DataFrame API, RDD concepts, optimization).




Solid
understanding of data modeling for OLTP/OLAP.
Proven
ETL/ELT pipeline design experience.
Cloud
experience (AWS preferred; similar GCP/Azure OK).
Knowledge
of data warehousing concepts and distributed systems.
Git
and CI/CD experience.
Solid
debugging, optimization, and problem-solving skills.
Ability
to work with large-scale datasets.

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Preferred Skills
Airflow/Dagster/Prefect
Kafka/Kinesis
or streaming systems
Docker/Kubernetes
IaC:
CDK, Terraform, CloudFormation
Delta
Lake, Iceberg, or Hudi
ML
feature pipelines
Monitoring
tools: CloudWatch, Datadog, Prometheus, ELK
System
design and architectural experience

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Soft Skills
Explicit
communication and documentation
Ownership
mindset
Mentorship
capability
Collaboration
with cross-functional teams
Detail
orientation and structured thinking

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Why Work With Us
High-impact
ownership of

📌 Senior Software Engineer Data Mumbai
🏢 Bandhan Life
📍 Mumbai