AWS ENGINEER – DATA PLATFORMS
At a glance
Mid-level Cloud role at LITIT. Remote, Lithuania · full-time.
Pay not stated Cloud salary
devopsroles summary, based on the employer's posting.
What you'll do
- Build and run AWS data pipelines, lakes and data mesh components for analytics and data products
- Create and tune PySpark jobs that process large-scale and time-series data
- Manage Glue workflows and use Glue Data Catalog and Lake Formation to handle schemas, access and metadata
- Connect systems through APIs and support event-driven workflows using AWS services
- Track platform health and improve data processing reliability, security, performance and cost
What you bring
- Hands-on AWS engineering experience, including Glue, Lake Formation, S3 and other named platform services
- A track record building and operating ETL or ELT pipelines and data lake, lakehouse or data mesh solutions
- Practical Spark and PySpark skills, plus strong Python development ability
- Experience with Apache Iceberg or Parquet, API integrations, and automated CI/CD deployments
Who this fits
This role suits a mid-level AWS data engineer who has delivered production data platforms and can work with analytics and product teams in Scrum. The position is remote in Lithuania. You should be ready for occasional domestic or international travel, sometimes at short notice.
From the employer
ABOUT THE COMPANY
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.
ABOUT THE ROLE
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.
RESPONSIBILITIES
Design, implement, and operate scalable, cloud-native data pipelines and platform components on AWS
Build and maintain ETL/ELT workflows, data lakes, and data mesh components
Develop, optimize, and troubleshoot PySpark-based data processing jobs for large-scale and time-series datasets
Design and manage data schemas, tables, permissions, and metadata using AWS Glue Data Catalog and Lake Formation
Develop and maintain AWS Glue Jobs for data ingestion, transformation, and orchestration
Build and support event-driven architectures leveraging AWS Lambda, SNS, SQS, and Step Functions
Integrate internal and external systems through APIs using AWS API Gateway and related services
Monitor platform health, performance, and operational metrics using Amazon CloudWatch
Ensure efficient, reliable, secure, and cost-effective data processing across the platform
Contribute to Infrastructure as Code, CI/CD pipelines, and automated deployment processes
Collaborate closely with data platform, analytics, and product teams in an Agile (Scrum) environment
REQUIREMENTS
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.
Nice to have:
Experience with Infrastructure as Code, preferably Terraform
Experience designing and managing AWS infrastructure through Terraform
Understanding of event-driven and serverless architectures
Basic understanding of machine learning concepts, ML lifecycle, and MLOps practices
Experience working with industrial IoT, telemetry, sensor, or time-series data
WHAT WE OFFER
Salary range: €4000 - €6000 (GROSS) / month.
Learning opportunities with compensated certificates, learning lunches, and language lessons.
Chance to switch projects after one year.
Team building twice a year.
Office in Vilnius, Lithuania that offers themed lunches and a pet-friendly environment.
Remote work opportunities.
Flexible time off depending on a project.
Seasonal activities with colleagues.
Additional health insurance and loyalty days for Lithuanian residents.
Referral bonuses.
Recognition of important occasions of your life.
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