Senior Data Engineer

Go Digital Technology Consulting; Mumbai; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Go Digital Technology Consulting in Mumbai seeks a Senior Data Engineer to design and build scalable data pipelines using PySpark and SQL within AWS cloud. You will collaborate with users and stakeholders to define requirements and translate them into robust data architectures.

The role demands 4-8 years of hands-on experience with big data technologies, Hive, Hadoop, and ETL/ELT processes, plus strong communication to influence technical decisions and ensure best practices across projects.

Qualifications

• 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.

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.

Skills

Advanced SQL

Python

Pandas

NumPy

PySpark

Shell scripting

Data-Modelling

Big data

Hadoop

Hive

ETL pipelines

Tools

AWS

Spark

Hive

Git

CI/CD

Job description

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.