> Markdown version of [/jobs/ext/2660023-sr-data-engineer](https://www.wearedevelopers.com/jobs/ext/2660023-sr-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Engineer - **Company:** ONEDOME GLOBAL, INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, BigQuery, Data as a Services, Information Engineering, Data Mining, Data Warehousing, Cursor (Graphical User Interface Elements), Amazon DynamoDB, Identity and Access Management, Python (Programming Language), PostgreSQL, Microsoft Dynamics, NoSQL, Operational Databases, Query Optimization, Standard Sql, Business Intelligence Development Studio, GitHub Copilot, Snowflake, Change Data Capture, Amazon Relational Database Service, Infrastructure Automation Frameworks, Cloudwatch, Terraform, Looker Analytics - **Published:** August 24, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=16e7886502273f96 ## About the Role * 5+ years of professional experience building and running production data pipelines end to end. * Data warehouse design and modelling, including dimensional modelling, slowly changing dimensions, incremental and full-refresh builds, and schemas analysts can query unaided. * Hands-on production experience with Redshift, including loading strategies, distribution and sort key design, workload management, query tuning and cost control. An equivalent columnar warehouse (Snowflake, BigQuery) is acceptable with a credible transfer story. * Experience running dbt in production, including testing, documentation and CI. * Strong SQL, including tuning analytical queries, and strong Python. * Experience with relational and NoSQL databases, including Postgres (with JSONB) and DynamoDB or equivalent, and real experience getting analytical value out of NoSQL stores through change data capture, export patterns, denormalisation and schema drift. * Hands-on experience designing, deploying and operating data services on AWS, including S3, Glue, Athena, Lambda, EventBridge, Kinesis/Firehose, RDS, IAM and CloudWatch. * Experience with infrastructure automation and observability, including infrastructure as code (Terraform). * Experience handling regulated personal data in the UK, including GDPR, retention and subject access requests. * Comfortable using AI coding assistants (e.g. Claude Code, Cursor, GitHub Copilot) as part of the development workflow. * Strong communication skills in English. Russian is a plus., * Microsoft Dynamics 365 or Dataverse data extraction (Synapse Link, Dataverse API). * Mortgage, property or financial services domain experience. * Experience with BI tooling such as Looker or Metabase. * Familiarity with managed ingestion tools such as Fivetran or Airbyte. * AWS certification. ## Description OneDome is a UK-based property technology company on a mission to make buying, selling and financing a home simpler and faster. Our platform connects homebuyers, estate agents, conveyancers and mortgage brokers into a single digital journey, and it is scaling quickly. We hold a great deal of data on how customers move through buying, financing and conveyancing, and very little of it can currently be queried in one place. This is our first dedicated data engineering role. You will own our data warehouse and the pipelines that feed it, decide what the data platform looks like, and become the person the business relies on for answers., * Develop and maintain our AWS-based data platform for a quickly scaling business. * Build and own our data warehouse and the pipelines that feed it from product, CRM and third-party systems. * Model data for analytics and reporting so analysts, product and leadership can rely on it, and keep those models tested and documented. * Contribute to architecture decisions and technical direction across the platform. * Ensure data quality, performance and scalability. * Own data protection obligations within our pipelines, including retention, deletion and subject access requests. * Collaborate with product managers, analysts and engineers across distributed teams to deliver high-impact solutions. * Leverage AI-powered engineering tools to accelerate delivery while maintaining high standards of quality, security and operational excellence. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Making Data Warehouses fast. 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