We are looking for an experienced and driven

Senior Data Engineer

with

6+ years

of hands-on experience designing, building, and scaling robust data pipelines. The ideal candidate will combine deep technical expertise in

PySpark, SQL, and Python

with strong business acumen, acting as a crucial bridge between complex data infrastructure and our business stakeholders.
Experience with platforms like

Dataiku (DataIQ)

is highly preferred to support rapid pipeline development and cross-functional collaboration.

Key Responsibilities
Pipeline Architecture & Development:

Design, build, and optimize scalable ETL/ELT data pipelines using Python, PySpark, and modern orchestration tools.
Dataiku (DataIQ) Integration:

Leverage visual and code-based recipes within Dataiku to rapidly prototype, deploy, and monitor end-to-end data workflows and machine learning pipelines.
Database Optimization:

Write, tune, and maintain highly complex SQL queries and data models to ensure high-performance analytical reporting.
Stakeholder Collaboration:

Partner directly with business units,



product managers, and leadership to understand data requirements, translate them into technical specifications, and present insights clearly.
Data Governance & Quality:

Ensure data integrity, reliability, and security across all pipelines through robust testing, monitoring, and best-practice implementation.
Mentorship:

Guide junior and mid-level engineers on best practices for coding, optimization, and scalable data architecture.

Required Qualifications & Skills
Experience:

6+ years of professional experience in data engineering, data warehousing, or software engineering focused on data systems.
Big Data Technologies:

Advanced proficiency in

PySpark

and distributed computing frameworks.
Database Expertise:

Exceptional SQL skills, including performance tuning, complex window functions, and schema design for contemporary cloud data warehouses.
Platform Preference:

Hands-on experience building pipelin

📌 Senior Data Engineer (Mumbai)
🏢 Mindtel
📍 Mumbai