Senior Data Engineer

Job Title:

About Edgematics

Edgematics Technologies is a leading global consulting and solutions integrator specializing in data management, business intelligence, and analytics. We deliver end-to-end data management solutions that enable organizations to make data-driven decisions and achieve their strategic objectives.

www.edgematics.ai

Job Overview

Senior Data Engineer (812 years)

This role requires strong technical depth, ownership, problem-solving capability, and the ability to work in a collaborative and fast-paced environment.

Key Responsibilities

• Design and implement scalable, high-performance data pipelines for batch and real-time data processing, ingestion, transformation, and storage.
• Architect, build, and maintain data models, schemas, and ETL/ELT processes ensuring data quality, consistency, and reliability across systems.
• Collaborate with data scientists, analysts, architects, and engineering teams to translate business requirements into scalable and efficient data solutions.
• Optimize data workflows, processing scripts, query logic, and storage layers for performance, scalability, and cost governance.
• Define and enforce data governance, data privacy, metadata management, and security standards aligned with compliance frameworks.
• Evaluate emerging data engineering tools, platforms, and frameworks to strengthen engineering capability and operational efficiency.
• Monitor, diagnose, and resolve production data issues, performance bottlenecks, and pipeline failures with cross-functional teams including DevOps.
• Document system designs, architectures, workflows, and processes to support cross-team knowledge sharing and operational continuity.
• Mentor junior and mid-level engineers and contribute to technical guidelines, best practices, and reusable frameworks.

Qualifications

• Bachelors or Master’s degree in Computer Science, Information Technology, or a related discipline.

• 7 –12 years of hands-on experience

  in data engineering, ETL/ELT development, and data warehousing within complex enterprise environments.
• Strong command of programming languages such as

  Python and SQL

  for scripting, automation, and data transformation tasks.
• Proven experience working with relational databases (SQL Server, PostgreSQL, MySQL) and cloud data platforms such as

  Snowflake

  .
• Strong experience with modern data engineering ecosystems including

  Hadoop, Spark, Kafka, Hive, HBase, or similar big data stacks

  .
• Hands-on experience with cloud platforms (

  AWS, Azure, or GCP

  ) including storage, compute, and analytics services.
• Solid understanding of data modeling, data architecture principles, integration patterns, and data lifecycle management.
• Experience working with

  CI/CD pipelines, Git-based version control

  , and Agile development methodologies.
• Strong problem-solving abilities with a track record of delivering high-impact and scalable data engineering solutions.
• Excellent communication, collaboration, and stakeholder management skills.

Preferred Experience

• Telecom / Fibre data domain experience (highly advantageous)
• Experience with real-time streaming and event-driven data systems
• Experience building reusable frameworks, accelerators, or automation tools within the data engineering function