Sr. Data Engineer
Team: Data Engineering
Location: Bengaluru, Karnataka
Commitment: Full-Time
Workplace Type: hybrid
How you will make an impact
- Lead the design and implementation of scalable, reusable ETL/ELT frameworks and data pipelines across multiple client environments.
- Define and enforce engineering best practices for data modeling, quality assurance, and performance optimization.
- Mentor and support Data Engineers, conducting peer reviews and ensuring alignment with architectural standards.
- Oversee the operational stability of production data pipelines, including monitoring, troubleshooting, and capacity planning.
- Partner with data architects and product teams to design end-to-end data solutions aligned to business goals.
- Conduct source data analysis and profiling to guide schema and model design decisions.
- Implement and optimize data models including slowly changing dimensions, transactional, accumulating snapshot, and periodic snapshot fact tables.
- Collaborate with platform engineers to evolve event-driven and streaming architectures supporting real-time analytics.
- Drive automation initiatives for testing, auditing, and metadata capture to ensure transparency and reproducibility
What you need to be successful
- 5–7 years of Data Engineering experience, with at least 3 years operating in Snowflake.
- Proven success designing and deploying large-scale data pipelines and dimensional models using modern cloud data platforms.
- Deep understanding of Kimball and Data Vault methodologies, and how they integrate within Lakehouse and event-driven architectures.
- Advanced proficiency with SQL and Python for pipeline development, data validation, and automation.
- Experience leading data engineering projects through the full SDLC, from requirements through deployment and monitoring. Expertise in integrating batch and streaming data sources, including Kafka, APIs, and message queues.
- Experience with orchestration and workflow management tools such as Airflow, Matillion or dbt.
- Cloud experience with Azure and/or AWS, including cost optimization and data security best practices.
- Strong communication and leadership skills to guide cross-functional teams and present technical concepts clearly to non-technical stakeholders.
- Value-add: familiarity with vector and graph databases, Apache NiFi, and modern data sharing or clean-room technologies.
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