Senior Data Engineer

Role: Senior Data Engineer

Location: Mumbai

Experience: 4yrs to 8yrs

Technologies / Skills: Advanced SQL, Python and associated libraries like Pandas, NumPy etc., Pyspark , Shell scripting, Data-Modelling, Big data, Hadoop, Hive, ETL pipelines.

Responsibilities: • Proven success in communicating with users, other technical teams, and

senior management to collect requirements, describe data modeling decisions and develop data

engineering strategy.

• Ability to work with business owners to define key business requirements and convert to user stories with required technical specifications.

• Communicate results and business impacts of insight initiatives to key stakeholders to

collaboratively solve business problems.

• Working closely with the overall Enterprise Data & Analytics Architect and Engineering practice leads to ensure adherence with the best practices and design principles.

• Assures quality, security and compliance requirements are met for supported area.

• Design and create fault-tolerance data pipelines running on cluster

• Excellent communication skills with the ability to influence client business and IT teams

• Should have design data engineering solutions end to end. Ability to come up with scalable and

modular solutions.

Required Qualification:

• 4+ years of hands-on experience Designing and developing Data Pipelines for Data Ingestion or

Transformation using Python (PySpark)/Spark SQL in AWS cloud

• Experience in design and development of data pipelines and processing of data at scale.

• Advanced experience in writing and optimizing efficient SQL queries with Python and Hive handling Large Data Sets in Big-Data Environments

• Experience in debugging, tunning and optimizing PySpark data pipelines

• Should have implemented concepts and have good knowledge of Pyspark data frames, joins,

caching, memory management, partitioning, parallelism etc.

• Understanding of Spark UI, Event Timelines, DAG, Spark config parameters, in order to tune the

long running data pipelines.

• Experience working in Agile implementations

• Experience with building data pipelines in streaming and batch mode.

• Experience with Git and CI/CD pipelines to deploy cloud applications

• Good knowledge of designing Hive tables with partitioning for performance.

Desired Qualification:

• Experience in data modelling.

• Hands on creating workflows on any Scheduling Tool like Autosys, CA Workload Automation.

• Proficiency in using SDKs for interacting with native AWS services.

• Strong understanding of concepts of ETL, ELT and data modeling.