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GeekSoft Consulting is an IT consulting and staff augmentation firm that provides specialized SAP and Salesforce consulting services to clients; the job postings are for billable, client-facing consulting roles.

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Posted 3w ago

Lead Data Engineer - AWS, Databricks & Graph Technologies

@ Geeksoft Consulting
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Bangalore, Karnataka, India
OnsiteContract
Responsibilities:designing platform, building pipelines, mentoring engineers
Requirements Summary:10+ years data engineering experience building cloud-native data platforms on AWS/Databricks; strong Spark, Kafka, SQL, Python, data modeling, ETL/ELT, and graph database experience; technical leadership and mentoring skills.
Technical Tools Mentioned:Amazon S3, Amazon Redshift, AWS Glue, Amazon Athena, AWS Lambda, Amazon DynamoDB, Amazon ECS/Fargate, AWS Step Functions, Amazon SNS/SQS, Apache Spark, Apache Kafka, SQL, Python, PostgreSQL, Oracle, SQL Server, MongoDB, Cassandra, Git, Docker, CI/CD pipelines, Infrastructure as Code (IaC), Databricks, Delta Lake, Unity Catalog, Snowflake, Microsoft Fabric, Neo4j, Amazon Neptune, GraphDB, Microsoft Azure
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Job Description
  • Help design, build and continuously improve the clients online platform.
  • Research, suggest and implement new technology solutions following best practices/standards.
  • Take responsibility for the resiliency and availability of different products.
  • Be a productive member of the team.



Requirements

  • Minimum 10 years of experience in Data Engineering.
  • Experienced Lead Data Engineer to design, develop, and implement modern cloud-native data platforms that enable analytics, artificial intelligence, and data-driven decision-making.
  • Work closely with architects, engineers, and business stakeholders to solve complex data challenges across diverse industries, including government, financial services, infrastructure, energy, and manufacturing.
  • As a technical leader, play a key role in defining data architecture standards, mentoring Data Engineers, and driving best practices within the Data & Analytics team.
  • Design and implement scalable Data Lakes, Data Warehouses, and Lakehouse architectures.
  • Develop and maintain robust ETL/ELT pipelines for both batch and real-time data processing.
  • Design and optimize data models while ensuring data quality, governance, and consistency.
  • Build and support cloud-native data solutions on AWS.
  • Develop event-driven and serverless architectures to support modern data platforms.
  • Enable analytics, business intelligence, artificial intelligence, and machine learning initiatives through efficient data solutions.
  • Provide technical leadership, mentor Data Engineers, and contribute to architecture and design decisions.
  • Collaborate within Agile teams to deliver innovative and scalable client solutions.
  • Strong experience designing and implementing cloud-native data platforms.
  • Deep understanding of Data Engineering principles, ETL/ELT processes, Data Modeling, and Data Warehousing concepts.
  • AWS Cloud Technologies: Amazon S3, Amazon Redshift, AWS Glue, Amazon Athena, AWS Lambda, Amazon DynamoDB, Amazon ECS/Fargate, AWS Step Functions, Amazon SNS/SQS
  • Data Engineering & Big Data Technologies: Apache Spark, Apache Kafka, SQL, Python
  • Relational databases such as PostgreSQL, Oracle, SQL Server, or equivalent.
  • NoSQL databases including MongoDB, DynamoDB, Cassandra, or similar platforms.
  • Engineering & DevOps: Git version control, Docker, CI/CD pipelines, Infrastructure as Code (IaC), Agile/Scrum methodologies
    Databricks & Modern Data Platforms: Databricks, Delta Lake, Unity Catalog, Lakehouse Architecture
  • Experience with Snowflake, Microsoft Fabric, or similar modern data platforms
  • Graph Technologies: Neo4j, Amazon Neptune, GraphDB, or similar graph databases, Graph Data Modeling, Graph Analytics, Knowledge Graphs, Data Lineage and Dependency Mapping
  • Additional Preferred Skills: Event-Driven Architecture, Microservices Architecture, Machine Learning and Advanced Analytics
  • Experience with Microsoft Azure Data Platform technologies
  • Bachelor’s or Master’s degree in Computer Science, Informatics, Data Science, Engineering, or a related field.
Certifications
  • AWS Certifications are highly valued.
  • Databricks Certifications are considered a strong advantage.




Benefits

  • A challenging, innovating environment.
  • Opportunities for learning where needed.