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

2 weeks ago


Delhi, Delhi, India Tech Mahindra Full time

Duration:
Long TermWorking Hours : 2pm to 11pm ISTBand : U3 or U4Working 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 ModellingGood to have but not mandatory

– Healthcare Domain experience, Snowflake.
Certifications (Good to have) –

None

Job DescriptionRequired Skills and QualificationsStrong programming skills in

Python , including experience with data libraries and frameworks, like

Pandas,
SQL Alchemy, Numpy, etcExperience with data pipeline orchestration tools like

Apache AirflowExpertise 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 pipelinesStrong 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 ResponsibilitiesDevelop 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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