Data Engineer

Job Title: Data Engineer

Experience Required:

About SID Global Solutions

BFSI, Healthcare, Retail, Manufacturing, and Public Sector

AI, Cloud, Automation, API Management, and Modern Data Platforms

About the Role:

Data Engineer

Key Responsibilities:

• Design, develop, and maintain robust

  ETL/ELT pipelines

  for structured and unstructured data.
• Build and optimize

  data warehouses, data lakes

  , and

  data models

  to support analytics and reporting needs.
• Work closely with

  data analysts, data scientists, and business teams

  to ensure data accuracy and availability.
• Implement

  data governance, quality, and security standards

  across the data ecosystem.
• Manage and optimize

  data storage and retrieval

  for high performance and scalability.
• Collaborate with cross-functional teams to

  migrate, integrate, and transform data

  across systems.
• Monitor and troubleshoot

  data pipeline performance

  , ensuring minimal downtime.
• Evaluate and implement new

  data tools, frameworks, and best practices

  to enhance data operations.

Required Skills & Qualifications:

• Bachelors or Master’s degree in

  Computer Science, Information Technology, Engineering

  , or related field.
• 6–8 years of experience in

  data engineering

  or similar roles.
• Proficiency in

  SQL

  and experience with relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB).
• Strong experience with

  ETL tools

  (e.g., Apache Airflow, Talend, Informatica, AWS Glue, dbt).
• Expertise in at least one

  programming language

  (Python, Scala, or Java).
• Hands-on experience with

  cloud data platforms

  — AWS (Redshift, S3, Glue), Azure (Data Factory, Synapse), or GCP (BigQuery, Dataflow).
• Familiarity with

  big data frameworks

  (Spark, Hadoop, Kafka).
• Experience with

  data modeling, schema design

  , and

  data warehousing concepts

  .
• Knowledge of

  CI/CD pipelines, containerization (Docker/Kubernetes)

  , and

  version control (Git)

  .

Good to Have:

• Experience with

  real-time streaming data

  solutions.
• Exposure to

  machine learning data pipelines

  or

  analytics platforms

  .
• Familiarity with

  data governance and cataloging tools

  (Collibra, Alation, Apache Atlas).
• Understanding of

  DevOps or MLOps

  principles in data environments.