Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills :
PySpark
Good to have skills :
NA
Minimum
5
year(s) of experience is required
Educational Qualification :
15 years full time education
Summary: As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to effectively migrate and deploy data across various systems, contributing to the overall efficiency and reliability of data operations. Roles and Responsibilities: Lead Development and Implementation of ETL Processes Using PYSpark: Design, develop, and optimize ETL pipelines for data ingestion, transformation, and loading into the data warehouse Design and Maintain Data Warehouse Solutions: Develop and maintain data warehouse schemas, tables, and views to support analytics and reporting needs Provide Technical Guidance and Mentorship to Junior Developers: Guide and support team members in their technical development, ensuring adherence to best practices and coding standards Collaborate with Stakeholders to Understand Data Requirements: Work closely with business users and other stakeholders to understand their needs and ensure data solutions meet their requirements Troubleshoot and Resolve Issues: Diagnose and resolve issues related to data processing, data quality, and data warehouse performance Contribute to the Development of Data Governance Policies: Help define and implement data governance policies to ensure data quality, security, and compliance Skills and Experience:Extensive Experience with PYSpark: Proficiency in Python programming, Spark architecture, Spark SQL, and Spark Data Frames Strong Knowledge of Data Warehousing Principles: Experience with data modeling, data warehousing architectures, and common data warehouse platforms (e.g., Snowflake, Redshift, BigQuery) SQL Proficiency: Strong SQL skills, including experience with relational databases and data modeling Experience with Cloud Platforms: Familiarity with cloud data warehousing services (e.g., AWS, Azure, Google Cloud) Leadership and Communication Skills: Ability to lead and motivate a team, communicate technical concepts clearly, and collaborate effectively with stakeholders Problem-Solving and Analytical Skills: Ability to diagnose and resolve complex technical issues Proven Ability to Deliver Data Solutions: Experience in designing, implementing, and maintaining data solutions Minimum Experience: At least 8 years of experience in data engineering or a related field. Professional & Technical Skills: - Must To Have Skills: Proficiency in PySpark. - Strong understanding of data pipeline architecture and design. - Experience with ETL processes and data integration techniques. - Familiarity with data quality frameworks and best practices. - Knowledge of cloud platforms and their data services. Additional Information: - The candidate should have minimum 5 years of experience in PySpark. - This position is based at our Pune office. - A 15 years full time education is required.
15 years full time education
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