O
Onhiresvia Ashby
Senior Data Engineer (AWS / Databricks)
REMOTEPosted 1d ago
Data EngineerSeniorFull-time
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About the Role
Remote (EU/Ukraine) | Full-time
We’re hiring on behalf of our client — an international product company building and scaling a portfolio of subscription-based digital products for global markets.
The company is now building a centralized data platform that will bring together fragmented product, payments, marketing, and operational data across its portfolio. They are looking for a hands-on Senior Data Engineer to help establish Databricks on AWS, define the platform’s core engineering standards, and build reliable data products for analysts and business stakeholders.
This is a greenfield platform role with substantial technical ownership. You will not be joining a mature data environment with established patterns. You will help design those patterns, make foundational technical decisions, and create a repeatable approach for onboarding new products and data sources.
Why this role is interesting
- Build a centralized data platform from an early stage rather than inherit a mature warehouse
- Influence architecture, engineering standards, ingestion patterns, and governance
- Solve a complex platform challenge involving distributed PostgreSQL databases across private AWS and EKS environments
- Build the first portfolio-wide data models around payments, subscriptions, revenue, churn, LTV, and CAC
- Work closely with Data, DevOps, Product, Backend Engineering, and business stakeholders
- See a direct connection between your engineering work and key product and commercial decisions
What you’ll do
Build the Data Platform
- Build and operate a Databricks-based data platform on AWS together with the Data and DevOps teams
- Design and maintain Bronze, Silver, and Gold data layers using S3 and Delta Lake
- Develop reusable ingestion patterns for PostgreSQL databases, S3, APIs, webhooks, and SaaS platforms
- Build and manage production workflows using Databricks Jobs and Workflows
- Contribute infrastructure changes through Terraform, Git, and pull-request-based workflows
- Help establish platform standards, development patterns, and technical documentation
Build Reliable Data Pipelines
- Implement incremental data loads, historical backfills, idempotent reprocessing, and schema-change handling
- Design safe ingestion from multiple production PostgreSQL databases without creating unnecessary risk or load for source applications
- Handle late-arriving updates, deletes, retries, and pipeline recovery
- Build monitoring, freshness checks, reconciliation processes, and data-quality controls
- Troubleshoot pipeline failures and data inconsistencies across multiple products and source systems
- Optimize Databricks compute, SQL workloads, and storage for performance, reliability, and cost
Unify Product and Payments Data
- Standardize fragmented product and payments data across the company’s portfolio
- Build common analytical entities for users, subscriptions, transactions, renewals, refunds, and chargebacks
- Normalize product-specific schemas into reliable source-of-truth models
- Deliver trusted Gold datasets and data marts for Payments, Marketing, Product, Finance, and executive reporting
- Support analytical use cases related to revenue, subscriptions, churn, LTV, CAC, product funnels, and attribution
Establish Governance and Engineering Standards
- Contribute to Unity Catalog implementation and ongoing governance
- Help manage groups, permissions, service principals, and data access patterns
- Apply Git-based development, code review, CI/CD, testing, and documentation practices
- Work with Product and Backend teams to understand source tables, relationships, and business logic
- Help define repeatable patterns for onboarding new products and data sources
Target Platform
- AWS
- Databricks
- Spark / PySpark
- S3
- Delta Lake
- Unity Catalog
- Databricks Jobs / Workflows
- PostgreSQL
- Python
- SQL
- Terraform
- Git and CI/CD
What we’re looking for
- Strong production experience in Data Engineering
- Advanced Python and SQL skills
- Hands-on production experience with Databricks and Spark/PySpark
- Practical AWS experience, particularly with S3 and IAM
- Experience ingesting data from PostgreSQL or other relational databases
- Strong understanding of incremental pipelines, historical backfills, idempotency, retries, and reprocessing
- Experience designing analytical data models and working with medallion architecture
- Experience implementing data-quality checks, monitoring, reconciliation, and troubleshooting
- Experience with Git-based development and CI/CD workflows
- Ability to take ownership of complex data initiatives from design through production operation
- Comfort working in a greenfield environment where standards, ingestion patterns, and models are still being defined
- Ability to collaborate effectively with DevOps, Backend Engineering, Product, Analytics, and business stakeholders
Strong advantages
- Experience with Terraform or another Infrastructure as Code tool
- Hands-on experience with Unity Catalog
- Experience with Databricks Jobs, Workflows, or Lakeflow
- Understanding of AWS networking, VPCs, and EKS environments
- Experience with CDC technologies such as AWS DMS or Debezium
- Experience working with subscription and payments data
- Familiarity with Stripe, Adyen, Solidgate, or other payment service providers
- Experience integrating marketing or attribution data
- Experience with dbt
- Previous responsibility for defining data-platform standards or reusable engineering patterns
- Experience building a data platform in a startup, scale-up, or other ambiguous environment
What success could look like
During your first stage in the role, you will help:
- Establish the core AWS, Databricks, S3, Unity Catalog, and Terraform platform foundation
- Productionize the first reusable end-to-end ingestion pattern
- Onboard and unify payments data across multiple products
- Deliver core Gold models for revenue, subscriptions, churn, and LTV
- Create and document a repeatable approach for onboarding additional products
- Put monitoring, reconciliation, CI/CD, and cost controls into production
What our client offers
- Competitive compensation
- Fully remote work with flexible working hours
- 22 paid vacation days plus local public holidays
- A modern engineering environment with contemporary technologies
- The opportunity to shape a growing Data function and its technical foundations
- Meaningful platform challenges with room to influence architecture and engineering practices
- A collaborative, product-focused environment where data directly supports business decision
We’re hiring on behalf of our client — an international product company building and scaling a portfolio of subscription-based digital products for global markets.
The company is now building a centralized data platform that will bring together fragmented product, payments, marketing, and operational data across its portfolio. They are looking for a hands-on Senior Data Engineer to help establish Databricks on AWS, define the platform’s core engineering standards, and build reliable data products for analysts and business stakeholders.
This is a greenfield platform role with substantial technical ownership. You will not be joining a mature data environment with established patterns. You will help design those patterns, make foundational technical decisions, and create a repeatable approach for onboarding new products and data sources.
Why this role is interesting
- Build a centralized data platform from an early stage rather than inherit a mature warehouse
- Influence architecture, engineering standards, ingestion patterns, and governance
- Solve a complex platform challenge involving distributed PostgreSQL databases across private AWS and EKS environments
- Build the first portfolio-wide data models around payments, subscriptions, revenue, churn, LTV, and CAC
- Work closely with Data, DevOps, Product, Backend Engineering, and business stakeholders
- See a direct connection between your engineering work and key product and commercial decisions
What you’ll do
Build the Data Platform
- Build and operate a Databricks-based data platform on AWS together with the Data and DevOps teams
- Design and maintain Bronze, Silver, and Gold data layers using S3 and Delta Lake
- Develop reusable ingestion patterns for PostgreSQL databases, S3, APIs, webhooks, and SaaS platforms
- Build and manage production workflows using Databricks Jobs and Workflows
- Contribute infrastructure changes through Terraform, Git, and pull-request-based workflows
- Help establish platform standards, development patterns, and technical documentation
Build Reliable Data Pipelines
- Implement incremental data loads, historical backfills, idempotent reprocessing, and schema-change handling
- Design safe ingestion from multiple production PostgreSQL databases without creating unnecessary risk or load for source applications
- Handle late-arriving updates, deletes, retries, and pipeline recovery
- Build monitoring, freshness checks, reconciliation processes, and data-quality controls
- Troubleshoot pipeline failures and data inconsistencies across multiple products and source systems
- Optimize Databricks compute, SQL workloads, and storage for performance, reliability, and cost
Unify Product and Payments Data
- Standardize fragmented product and payments data across the company’s portfolio
- Build common analytical entities for users, subscriptions, transactions, renewals, refunds, and chargebacks
- Normalize product-specific schemas into reliable source-of-truth models
- Deliver trusted Gold datasets and data marts for Payments, Marketing, Product, Finance, and executive reporting
- Support analytical use cases related to revenue, subscriptions, churn, LTV, CAC, product funnels, and attribution
Establish Governance and Engineering Standards
- Contribute to Unity Catalog implementation and ongoing governance
- Help manage groups, permissions, service principals, and data access patterns
- Apply Git-based development, code review, CI/CD, testing, and documentation practices
- Work with Product and Backend teams to understand source tables, relationships, and business logic
- Help define repeatable patterns for onboarding new products and data sources
Target Platform
- AWS
- Databricks
- Spark / PySpark
- S3
- Delta Lake
- Unity Catalog
- Databricks Jobs / Workflows
- PostgreSQL
- Python
- SQL
- Terraform
- Git and CI/CD
What we’re looking for
- Strong production experience in Data Engineering
- Advanced Python and SQL skills
- Hands-on production experience with Databricks and Spark/PySpark
- Practical AWS experience, particularly with S3 and IAM
- Experience ingesting data from PostgreSQL or other relational databases
- Strong understanding of incremental pipelines, historical backfills, idempotency, retries, and reprocessing
- Experience designing analytical data models and working with medallion architecture
- Experience implementing data-quality checks, monitoring, reconciliation, and troubleshooting
- Experience with Git-based development and CI/CD workflows
- Ability to take ownership of complex data initiatives from design through production operation
- Comfort working in a greenfield environment where standards, ingestion patterns, and models are still being defined
- Ability to collaborate effectively with DevOps, Backend Engineering, Product, Analytics, and business stakeholders
Strong advantages
- Experience with Terraform or another Infrastructure as Code tool
- Hands-on experience with Unity Catalog
- Experience with Databricks Jobs, Workflows, or Lakeflow
- Understanding of AWS networking, VPCs, and EKS environments
- Experience with CDC technologies such as AWS DMS or Debezium
- Experience working with subscription and payments data
- Familiarity with Stripe, Adyen, Solidgate, or other payment service providers
- Experience integrating marketing or attribution data
- Experience with dbt
- Previous responsibility for defining data-platform standards or reusable engineering patterns
- Experience building a data platform in a startup, scale-up, or other ambiguous environment
What success could look like
During your first stage in the role, you will help:
- Establish the core AWS, Databricks, S3, Unity Catalog, and Terraform platform foundation
- Productionize the first reusable end-to-end ingestion pattern
- Onboard and unify payments data across multiple products
- Deliver core Gold models for revenue, subscriptions, churn, and LTV
- Create and document a repeatable approach for onboarding additional products
- Put monitoring, reconciliation, CI/CD, and cost controls into production
What our client offers
- Competitive compensation
- Fully remote work with flexible working hours
- 22 paid vacation days plus local public holidays
- A modern engineering environment with contemporary technologies
- The opportunity to shape a growing Data function and its technical foundations
- Meaningful platform challenges with room to influence architecture and engineering practices
- A collaborative, product-focused environment where data directly supports business decision
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