Senior Data Engineer

Worktual Innovations

Chennai District

On-site

INR 2,500,000 - 4,200,000

Full time

14 days+

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Job summary

Worktual Innovations is seeking a Senior Data Engineer in Chennai to design, build, and optimize enterprise-scale data platforms and pipelines. You will work on PostgreSQL, MySQL, ETL/ELT development, data modeling, and cloud data platforms while ensuring high availability, security, and data quality.

You will collaborate with software engineers, data scientists, DevOps teams, and stakeholders to deliver reliable, high-performance data ecosystems across transactional apps, analytics, and AI/ML

Qualifications

6+ years of experience in designing, building, and optimizing enterprise-scale data platforms, databases, and data pipelines.
Strong expertise in PostgreSQL and MySQL, ETL/ELT development, data modeling, and performance optimization.
Experience with cloud data platforms and distributed data processing.

Responsibilities

Design, develop, and maintain enterprise-scale data platforms and data pipelines.
Build scalable ETL/ELT workflows for ingesting, transforming, and integrating data from multiple sources.
Design and optimize relational databases using PostgreSQL and MySQL.
Develop reusable data integration frameworks and automation processes.
Build data ingestion pipelines for structured, semi-structured, and unstructured datasets.
Implement data validation, cleansing, enrichment, and transformation processes.

Skills

SQL

Python

Shell scripting

PL/pgSQL

Stored Procedures

Functions

Education

Bachelor's or Master's degree in CS/IT/Data Engineering

Tools

Databricks

Snowflake

dbt

Kubernetes

Docker

Airflow

Kafka

Spark

Job description

Job Summary

We are seeking a highly skilled Senior Data Engineer with 6+ years years of experience in designing, building, and optimizing enterprise-scale data platforms, databases, and data pipelines. The ideal candidate should possess deep expertise in PostgreSQL, MySQL, ETL/ELT development, data modeling, Databricks, Snowflakes, DBT, performance optimization, cloud data platforms, and distributed data processing.

The role involves architecting scalable data solutions that support transactional applications, analytics, AI/ML initiatives, and enterprise reporting while ensuring high availability, security, and data quality.

The candidate will collaborate with software engineers, solution architects, data scientists, DevOps teams, and business stakeholders to build reliable, secure, and high-performance data ecosystems.

Key Responsibilities

Data Engineering & Platform Development

Design, develop, and maintain enterprise-scale data platforms and data pipelines.
Build scalable ETL/ELT workflows for ingesting, transforming, and integrating data from multiple sources.
Design and optimize relational databases using PostgreSQL and MySQL.
Develop reusable data integration frameworks and automation processes.
Build data ingestion pipelines for structured, semi-structured, and unstructured datasets.
Implement data validation, cleansing, enrichment, and transformation processes.
Design data lakes, operational data stores (ODS), and analytical data marts.

Database Engineering

Design normalized and denormalized database schemas.
Create and maintain tables, indexes, partitions, materialized views, stored procedures, functions, and triggers.
Perform query optimization and SQL tuning for high-volume transactional workloads.
Optimize indexing strategies and execution plans.
Design partitioning strategies for large datasets.
Implement replication, clustering, and high-availability architectures.
Plan and execute database migrations and version upgrades.
Monitor database performance and proactively resolve bottlenecks.
Perform capacity planning and database health monitoring.

Data Modeling

Design conceptual, logical, and physical data models.
Develop enterprise data models aligned with business domains.
Define master data, reference data, and metadata standards.
Ensure data consistency and integrity across systems.
Implement Slowly Changing Dimensions (SCD), star schemas, and snowflake schemas where applicable.

Data Pipeline & Integration

Develop high-performance data pipelines using ETL/ELT frameworks.
Integrate data from APIs, applications, databases, streaming platforms, and cloud services.
Build batch and real-time data processing solutions.
Design event-driven data ingestion pipelines.
Automate workflow scheduling and orchestration.

Performance Optimization

Analyze and optimize complex SQL queries.
Identify performance bottlenecks using execution plans.
Optimize storage utilization and indexing strategies.
Improve data loading performance.
Optimize large-scale reporting queries.

Security & Governance

Implement database security best practices.
Configure role-based access control (RBAC).
Implement Row-Level Security (RLS) where applicable.
Manage encryption at rest and in transit.
Ensure compliance with security and governance policies.
Design backup, recovery, and disaster recovery strategies.

Cloud & DevOps

Design cloud-native database architectures.
Automate database deployments using CI/CD pipelines.
Implement Infrastructure as Code (IaC) where applicable.
Monitor cloud database resources and optimize costs.
Support containerized database deployments.

Collaboration

Collaborate with Software Engineers, Architects, Product Teams, and Data Scientists.
Participate in solution architecture and technical design discussions.
Review database designs and coding standards.
Mentor junior engineers and conduct knowledge-sharing sessions.
Drive database best practices across engineering teams.

Required Technical Skills

Databases