Lead Data Engineer

ADA; Bengaluru; Presencial; INR 2 500 000 - 4 000 000; Tempo integral

Resumo da oferta

ADA is seeking a Lead Data Engineer to spearhead the design, build, and operation of a production-grade data platform in Bengaluru. You will own end‑to‑end pipelines, set engineering standards, and mentor a team delivering data for analytics, ML, and product use cases.

You will lead ETL/ELT pipelines, data modelling across PostgreSQL, Supabase and Cassandra, and orchestrate workflows on Apache Airflow. AWS-based deployment and strong governance practices are essential for success.

Qualificações

• 5–8 years of data engineering experience with leadership

Responsabilidades

• Lead and mentor a team of Data Engineers: code reviews, design reviews, growth plans
• Design and operate ETL/ELT pipelines in Python for batch and streaming workloads
• Own data modelling across PostgreSQL, Supabase and Cassandra
• Build and run orchestration on Apache Airflow with DAG design, SLAs and retries
• Deploy and operate the platform on AWS (EC2-based, self-managed stack)
• Establish data governance: catalog, lineage, ownership, MDM, data quality, observability
• Drive engineering excellence: Agile delivery, CI/CD, testing, IaC, code review

Conhecimentos

Python

SQL

Airflow

Data modeling

ETL/ELT pipelines

AWS

CI/CD

Agile

Formação académica

Bachelor's or Master's in Computer Science or related field

Ferramentas

PostgreSQL

Supabase

Apache Cassandra

Descrição da oferta de emprego

About ADA

ADA is the Data and AI Experience Company. We work with global enterprises to build data and AI powered experiences where every decision runs on real-time intelligence and every interaction earns trust. That's how businesses scale, stay ahead, and deliver measurable outcomes. Our mission is ambitious: to create the world’s most intelligent growth platform for every client we serve. With over 1500+ customers across Retail, Food and Beverage, CPG, Telecommunications, Financial Services, Healthcare and Automotive, we operate in 35 markets around the world.

Lead Data Engineer

• Experience: 5–8 years | Location: Bangalore/India | Type: Full-time

Lead the design, build, and operations of a production-grade data platform. Own end-to-end pipelines, set engineering standards, and mentor a team of Data Engineers delivering data for analytics, ML, and product use cases.

Responsibilities

• Lead & mentor a team of Data Engineers — code reviews, design reviews, growth plans
• Design and operate ETL/ELT pipelines in Python for batch and streaming workloads
• Own data modelling across PostgreSQL / Supabase (OLTP) and Cassandra (wide-column)
• Build and run orchestration on Apache Airflow — DAG design, SLAs, retries, backfills
• Deploy and operate the platform on AWS (EC2-based, self-managed stack)
• Establish data governance: catalog, lineage, ownership, MDM, data quality, profiling, observability
• Drive engineering excellence — Agile delivery, CI/CD, testing, IaC, code review

Product Mindset

Treat the data platform as a long-lived product, not a project:

• Own outcomes across the full lifecycle — design, delivery, operations, iteration
• Optimise for scale, reliability, and maintainability with measurable SLAs and cost targets
• Prioritise based on user value (analytics, ML, product teams as customers)
• Ship iteratively; measure adoption, quality, and reliability continuously

Must-Have

• 5–8 years in data engineering with proven experience leading and mentoring engineers
• Expert Python and strong SQL
• Production experience with PostgreSQL, Supabase, and Apache Cassandra
• Hands‑on ownership of Apache Airflow at scale
• Comfortable running data workloads on AWS EC2 (Linux, networking, self-managed services)
• Strong ETL, data modelling, orchestration fundamentals
• Practical experience implementing data governance — MDM, data quality, data profiling, observability, lineage/catalog
• Agile, CI/CD, and coding best practices as everyday habits

Good-To-Have

• Data security and compliance — encryption (KMS/at‑rest/in‑transit), PII handling, GDPR/PDPA
• Streaming (Kafka, Kinesis) and lakehouse (Iceberg, Delta) exposure
• IaC (Terraform, Ansible) for self-managed AWS stacks

Education

Bachelor's or Master's in Computer Science, Engineering, or related field.

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