Data Engineer

Data Engineer (35 Years Experience)

Location: Bengaluru, India (or as applicable)

Experience: 35 years

Compensation: Up to INR 18-20 lakhs per annum, subject to negotiations

Role Overview

We are seeking a hands-on Data Engineer with 35 years of experience in building scalable data pipelines, data warehouses, and cloud-based analytics platforms. The ideal candidate has strong SQL and Python skills, along with practical experience in ETL/ELT development, Apache Airflow orchestration, cloud data platforms, enterprise data modelling, and Teradata environments.

The role involves working closely with analytics, AI/ML, and business teams to deliver reliable, production-grade data solutions.

Core Skills & Experience

• SQL - Advanced SQL development including joins, CTEs, window functions, query optimization, stored procedures, and complex data transformations
• Python - Strong Python programming for ETL pipelines, automation scripts, API integrations, and data processing workflows
• ETL/ELT - Experience building robust data ingestion and transformation pipelines from APIs, databases, flat files, and cloud sources
• Apache Airflow: Hands-on experience designing and maintaining DAGs, scheduling workflows, managing dependencies, retries, and monitoring pipelines
• Cloud Platforms: Practical experience working with AWS, Azure, or GCP data services and cloud-native data architectures
• Data Modelling: Strong understanding of dimensional modelling including star schemas, fact/dimension tables, normalization, and data warehouse design principles
• Teradata (preferrable but not mandatory): Hands-on experience working with Teradata for enterprise data warehousing, large-scale SQL processing, and performance optimization

Typical Responsibilities

• Build and maintain scalable ETL/ELT pipelines
• Develop and optimize SQL transformations and warehouse queries (including Teradata environments)
• Create Airflow DAGs for orchestration and scheduling
• Design source-to-target mappings and curated data layers
• Support reporting, dashboards, and analytics use cases
• Work with structured and semi-structured datasets
• Monitor pipeline health, failures, and data quality
• Collaborate with BI, analytics, and AI/ML teams
• Contribute to cloud-based data platform development
• Maintain technical documentation and data lineage

Preferred Technical Stack

Languages

• Python
• SQL

Orchestration

• Apache Airflow

Cloud Platforms

At least one of:

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform (GCP)

Databases / Warehouses

• Snowflake
• BigQuery
• Redshift
• SQL Server
• PostgreSQL
• Teradata

Data Processing

• Pandas
• PySpark (nice to have)

Version Control

• Git

Good Indicators of a Strong Candidate

• Has built production-grade pipelines end-to-end
• Strong experience working with Teradata-based enterprise data environments
• Understands performance optimization and debugging
• Can independently write complex SQL
• Comfortable working with cloud-native data services
• Understands how data supports reporting and AI workflows
• Has worked with enterprise-scale datasets
• Demonstrates strong problem-solving and ownership

Educational Background

Bachelors or Masters degree in:

• Computer Science
• Engineering
• Data Science
• Mathematics
• Information Systems

Equivalent practical experience is acceptable.

Ideal Experience Examples

The candidate may have previously:

• Migrated on-premise ETL (including Teradata-based systems) to cloud
• Built reporting pipelines for finance, risk, or operations
• Developed Airflow-based orchestration frameworks
• Created warehouse models for BI dashboards
• Integrated APIs and external data feeds
• Supported AI/ML feature pipelines

What We Are NOT Looking For

• Pure BI developers focused only on dashboards
• Pure Data Scientists without engineering experience
• Candidates with only academic ML exposure and limited production engineering experience
• Candidates lacking strong SQL fundamentals