Senior Data Engineer (EU, EMEA Remote)

SavvyMoney is a US based leading financial technology company. We provide integrated credit score and personal finance solutions to 1,600 + bank and credit union partners throughout the United States. The SavvyMoney solutions integrate with more than 43 digital banking platforms.

SavvyMoney was recently recognized by the San Francisco Business Times and the Silicon Valley Journal as one of the "Top 25 Places to Work in the San Francisco Bay Area" and is an Inc. 5000 Fastest Growing Company.

Our company is growing and we are looking for Independent Senior Data Engineer Contractors to help support the growth.

**These Independent Contractors will work 100% Remotely from your home office in Poland, Romania or Portugal as part of a distributed team in the USA, Canada, Europe and several locations in India.

As a Senior Data Engineer at SavvyMoney, you will lead the design and evolution of our cloud-native data platform, focused on scalable batch processing, event-driven workflows, and tight integration with backend microservices.

You will work across the full data lifecycle - from ingestion to transformation to serving - while collaborating closely with software engineers to build data-intensive systems that power analytics, reporting, and product features.

This role requires strong experience in AWS, distributed systems, and backend engineering (particularly Java-based services), with an emphasis on reliability, performance, and maintainability.

Responsibilities -

Design, build, and own batch-oriented data pipelines and ETL workflows using:

AWS Glue for distributed processing

AWS Lambda and AWS Step Functions for orchestration

Amazon S3 as the central data lake

Develop and optimize ingestion pipelines using AWS-native services such as AppFlow, DMS, and limited use of Kinesis/Firehose for ingestion

Build and maintain analytical data models and query layers using:

Amazon Athena

Amazon Redshift

ClickHouse

Design and integrate data workflows with backend microservices running on Amazon ECS

Collaborate with backend engineers to build and extend microservices that expose data capabilities via APIs

Contribute to event-driven architectures using services such as EventBridge to coordinate data processing and system interactions

Ensure data quality, lineage, and observability through validation frameworks, monitoring, and alerting

Optimize performance across the stack (Glue jobs, Athena queries, Redshift workloads, ClickHouse schemas)

Implement best practices for:

Infrastructure as Code (Serverless/CloudFormation, Terraform)

CI/CD pipelines for data and services

Security, governance, and PII handling

Mentor engineers and contribute to architectural decisions and technical strategy

Requirements -

8+ years of experience in data engineering, backend engineering, or a hybrid role

Strong hands-on experience with AWS, including:

AWS Glue

AWS Lambda

AWS Step Functions

Amazon S3

Amazon Athena

Amazon Redshift

Experience building batch data pipelines and ETL systems at scale

Strong programming skills in:

Java (for microservices development)

Python (for data pipelines and Glue jobs)

Experience working with containerized services and orchestration via Amazon ECS

Experience designing or working within microservices architectures

Familiarity with event-driven systems (e.g., SQS, EventBridge)

Strong SQL skills and experience optimizing analytical queries

Experience with distributed processing frameworks (e.g., Spark via Glue)

Deep understanding of:

Data modeling (analytical and operational)

Partitioning and storage strategies

Performance tuning across multiple data systems

Nice to have -

Experience with Apache Airflow or similar orchestration tools

Experience with Cube Semantic Layer

Experience with ClickHouse at scale (schema design, query optimization)

Experience with financial or credit data systems

Familiarity with data quality frameworks

AWS certifications (Solutions Architect, Developer, or Data Analytics)