Python Data Engineer/ Immediate joiner(Python- Airflow-SQL)

1 month ago


India Tech Mahindra Full time

Duration: Long Term

Working Hours: 2pm to 11pm IST

Band: U3 or U4

Working Location: Remote - PAN INDIA (preferably near to Tech M office)

Experience: 6-12 Years


Key words to search for the candidate.

Mandatory – Python, Airflow, SQL, Data Modelling

Good to have but not mandatory – Healthcare Domain experience, Snowflake.

Certifications (Good to have) – None


Job Description

Required Skills and Qualifications

  • Strong programming skills in Python, including experience with data libraries and frameworks, like Pandas, SQL Alchemy, Numpy, etc
  • Experience with data pipeline orchestration tools like Apache Airflow
  • Expertise in SQL and database development, with the ability to write complex queries and optimize database performance.
  • Solid understanding of data modeling principles and best practices.
  • Experience of data warehouse & ETL technologies like Snowflake.
  • Source control - Git (daily commits, PR process, etc)
  • Knowledge on CI/CD pipelines
  • Strong communication and collaboration skills, with the ability to work in a team environment.
  • Bachelor’s or Master’s degree in computer science, Information Technology, or a related field.



Key Responsibilities

Develop complex SQL queries and scripts to support data transformation, aggregation, and analysis.

  • Utilize Python for automating data processes, integrating data systems, and building advanced analytics models.
  • Design and implement robust, scalable data pipelines and architectures in Snowflake, optimizing data flow and collection for cross functional teams.
  • Lead data modeling initiatives, ensuring the integrity and efficiency of data structures.
  • Collaborate with cross functional teams to understand data needs, gather requirements, and deliver data driven solutions that align with business goals.
  • Implement data security and compliance measures, adhering to industry standards and regulations.
  • Conduct data analysis and provide insights to support decision making and strategy development.
  • Stay abreast of emerging technologies and trends in data engineering, recommending, and implementing improvements to our data systems and processes.



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