Data Engineer

Key Responsibilities

• Design, develop, and maintain

  ETL/ELT pipelines

  to ingest, transform, and load data.
• Write efficient

  SQL queries

  for data extraction, transformation, and reporting.
• Develop scripts and automation using

  Python

  for data processing and workflow orchestration.
• Collaborate with data analysts, BI developers, and business teams to deliver reliable datasets.
• Ensure

  data quality, integrity, and consistency

  across different systems.
• Work with cloud and on-premise data platforms as required
• Document processes, data flows, and technical solutions for ongoing knowledge sharing.

Required Skills & Qualifications

• Basic proficiency in

  SQL

  (writing queries, joins, aggregations, data manipulation).
• Knowledge of

  Python

  for data processing and scripting.
• Understanding of

  data warehousing concepts

  (tables, schemas, ETL).
• Familiarity with version control tools (e.g.,

  Git

  ).
• Strong problem-solving and analytical mindset.
• Eagerness to learn and work with modern

  data engineering tools and cloud technologies

  .

Nice-to-Have Skills (Good to Learn/Have)

• Experience with

  cloud platforms

  (Azure Data Factory, AWS Glue, GCP Dataflow).
• Exposure to

  big data frameworks

  (Spark, Databricks, Hadoop).
• Basic knowledge of

  data visualization tools

  (Power BI, Tableau, etc.).
• Awareness of

  data goverce and data quality frameworks

  .