About the Company

Location: Bangalore

WorkMode: Hybrid

Experience: 5–8 years

Job Type: Full-time

About the Role

We’re looking for seasoned data engineers who can take end-to-end ownership of complex data engineering engagements—right from architecture and design to development and delivery. You’ll work with client stakeholders, lead data initiatives, and guide teams in building modern, scalable data platforms that support business intelligence, advanced analytics, and AI/ML applications.

Responsibilities

Lead the design and implementation of scalable, secure, and high-performance data architectures.
Architect and optimise data pipelines for batch and real-time processing across varied source systems.
Model and implement enterprise-grade data lakes, lakehouses, and warehouses to support analytical workloads.
Collaborate with client teams and internal stakeholders to define data strategies, tooling, and standards.
Set up and enforce best practices around code quality, pipeline observability, testing, and CI/CD.




Guide technical decision-making and mentor junior/mid-level engineers.
Troubleshoot complex data issues and provide architectural solutions across heterogeneous systems.

Qualifications

Robust expertise in Python and advanced proficiency in SQL.
Hands-on experience with Databricks.
Deep understanding of data engineering architecture: ETL/ELT pipelines, data modeling (dimensional and normalised), warehousing, streaming systems, and data integration patterns.
Proven experience with distributed data processing frameworks (e.g., Apache Spark, Flink).
Proficient with orchestration tools like Airflow or similar, and production-grade data workflows.
Solid grounding in cloud-native data services (compute, storage, IAM, monitoring).
Experience leading technical implementations and collaborating with business stakeholders.

Required Skills

Multi-cloud experience (AWS preferred; GCP or Azure familiarity is valued).
Hands-on experience with Databricks, dbt, and c

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