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AWS Data Engineer

2 months ago

bangalore, India Synechron Full time

Job Title: Senior Data Engineer - AWS, Python, PySpark, Hive, SQL
Location: Pune/Bangalore
Experience Required: 7+ years
Role Summary: As a Senior Data Engineer, you will lead the design and implementation of scalable, high-performance data solutions on AWS. You will leverage your deep expertise in Python, PySpark, Hive, and SQL to build and optimize data pipelines, support data modeling, and contribute to the architecture that supports big data processing and analytics.
Key Responsibilities:
Design and develop robust, scalable data pipelines using AWS services, Python, PySpark, Hive, and SQL.
Optimize data processing and storage for performance and cost.
Implement data security and compliance best practices in collaboration with the IT security team.
Lead the migration of legacy data warehouses and data marts to AWS cloud-based data lake and data warehouse solutions.
Work closely with data scientists and analysts to support their data needs and assist in building complex queries and data analysis pipelines.
Create and maintain comprehensive documentation of data pipelines, architectures, and workflows.
Continuously evaluate new technologies and AWS services to enhance data capabilities and performance.
Collaborate with cross-functional teams to understand their data needs and translate them into technical requirements.
Participate in code reviews and ensure that all solutions are aligned to pre-defined architectural specifications.
Provide mentoring and guidance to junior data engineers and team members.
Day-to-Day Activities:
Engage in daily stand-up meetings to discuss progress, obstacles, and timelines.
Design, code, test, and deploy new data pipelines and enhancements to existing pipelines.
Perform data modeling and ETL development as required for ongoing projects.
Monitor AWS resources and optimize the cost and performance of data applications.
Conduct data analysis and troubleshooting on complex data processing issues.
Collaborate with BI and analytics teams to assist in data-related technical issues and support their data infrastructure needs.
Lead performance tuning activities on SQL queries and PySpark jobs.
Ensure the integrity and availability of data by implementing proper backup and disaster recovery strategies.
Remain up-to-date with industry trends and advancements in big data and cloud computing.
Qualifications:
Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field.
7+ years of experience in a data engineering role with a strong focus on AWS, Python, PySpark, Hive, and SQL.
Proven experience in designing and delivering large-scale data warehousing and data processing solutions.
Strong understanding of AWS services such as S3, EC2, EMR, RDS, Redshift, Glue, Lambda, and Athena.
Deep knowledge of big data technologies and ETL tools.
Excellent problem-solving, analytical, and communication skills.
Ability to work independently as well as part of a team in a fast-paced environment.
Preferred Qualifications:
AWS certifications related to data engineering or architecture.
Experience with additional big data technologies like Kafka, Spark Streaming, or Hadoop.
Familiarity with machine learning concepts and tools.