Location: Pune / Mumbai / Bangalore / Chennai / Hyderabad / (Hybrid)

Notice Period : upto 60days

Key Responsibilities:

Python Proficiency:

● Demonstrate a strong command of Python programming language, actively contributing to the

development and maintenance of data engineering solutions.

Data Engineering Expertise:

● Set up and maintain efficient data pipelines, ensuring smooth data flow and integration across

systems. Experience with SQL and Data Warehouse/ Data Lakes is required. Contribute to the

establishment and maintenance of Data Lakes, implementing industry best practices. Execute

data scrubbing techniques and implement data validation processes to ensure data integrity

and quality.

Tool and Platform Proficiency:

● Experience with PySpark and/or Data Bricks platform is required, apart from this expertise in at

least one popular tool/platform within the data engineering domain will be nice to have. Stay

informed about industry trends, exploring and adopting tools to optimize data engineering

processes.

Collaboration and Communication:

● Collaborate effectively with cross-functional teams, including data scientists,

software engineers, and business analysts. Communicate technical concepts to non

technical stakeholders, fostering collaboration and innovation within the team.

Documentation and Best Practices:

●Contribute to maintaining comprehensive documentation for data engineering processes,

ensuring knowledge transfer within the team. Adhere to best practices in data engineering,

promoting a culture of quality and efficiency.

Must-Have Skills:

● Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

● Minimum of 4 years of proven experience as a Data Engineer.

● Strong proficiency in Python programming language and SQL.

● Experience in setting up and managing data pipelines, data warehouses/lakes.

● Good comprehension and critical thinking skills

Nice-to-Have Skills(Optional):

● Exposure to cloud-based data platforms (AWS/Azure/GCP) and pyspark.

● Basic knowledge of big data technologies such as Hadoop or Spark or Snowflake.

● Familiarity with containerization tools like Docker or Kubernetes.

● Interest in data visualization tools. (Tableau, PowerBI, etc.)

● Certificationsin relevant data engineering or machine learning technologies.