AWS ENGINEER – DATA PLATFORMS

LITIT, a joint venture between NTT DATA and Reiz Tech, is a company with deep-rooted industry know-how, dedicated to innovation within the IT sector. Its primary focus is delivering high-quality solutions in the DACH region. With a commitment to excellence, LITIT combines the best of German precision, Japanese work ethics, and Lithuanian talent to provide unparalleled IT service and support to its clients.

We are looking for an experienced AWS Data Engineer to join the development of our IoT Insurance Data Platform (IDP). In this role, you will design, build, and optimize scalable, cloud-native data solutions that power analytics, data products, and machine learning use cases in an industrial IoT and insurance environment. You will work in a modern AWS ecosystem, contributing to a data platform built on lakehouse principles, enabling high-performance data processing, governed data access, and event-driven data workflows. The ideal candidate combines strong AWS engineering expertise with hands-on experience in data platforms, distributed processing, and infrastructure automation.

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  Design, implement, and operate scalable, cloud-native data pipelines and platform components on AWS

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  Build and maintain ETL/ELT workflows, data lakes, and data mesh components

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  Develop, optimize, and troubleshoot PySpark-based data processing jobs for large-scale and time-series datasets

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  Design and manage data schemas, tables, permissions, and metadata using AWS Glue Data Catalog and Lake Formation

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  Develop and maintain AWS Glue Jobs for data ingestion, transformation, and orchestration

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  Build and support event-driven architectures leveraging AWS Lambda, SNS, SQS, and Step Functions

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  Integrate internal and external systems through APIs using AWS API Gateway and related services

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  Monitor platform health, performance, and operational metrics using Amazon CloudWatch

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  Ensure efficient, reliable, secure, and cost-effective data processing across the platform

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  Contribute to Infrastructure as Code, CI/CD pipelines, and automated deployment processes

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  Collaborate closely with data platform, analytics, and product teams in an Agile (Scrum) environment

• Strong hands-on experience with AWS services, including:

  • AWS Glue (Jobs and Data Catalog)

  • Lake Formation

  • AWS Lambda

  • Amazon S3

  • Amazon Athena

  • AWS Step Functions

  • Amazon DynamoDB

  • Amazon API Gateway

  • Amazon CloudWatch

  • Amazon SNS and SQS

• Proven experience in data engineering, including designing, building, and operating ETL/ELT pipelines

• Strong experience working with data lakes, lakehouse architectures, and/or data mesh concepts

• Solid hands-on experience with Spark and PySpark for distributed data processing and performance optimization

• Strong Python development skills

• Experience with modern data formats such as Apache Iceberg and Parquet

• Experience integrating and consuming APIs and data exchange services

• Experience with CI/CD pipelines and automated deployment practices

• Experience working in cross-functional Agile (Scrum) teams

• Proven ability to deliver production-grade, scalable, and maintainable cloud data solutions

• Willingness and readiness to travel as required by project or client needs is expected. This may include occasional domestic or international travel, sometimes on short notice.