Data Engineer

Reports to Chief Technology Officer (CTO)

Job Summary:

• As a Software Engineer working on our data platform, you’ll design, build and operate the data systems that support our products, analytics, and internal teams.
• This role sits at the intersection of software engineering, data engineering, and platform infrastructure. You’ll be responsible for the reliability, scalability, and evolution of our data platform – from operational databases and ingestion pipelines, through transformation, analytics, and reporting systems.
• You’ll work closely with engineering, product, QA, and business stakeholders to ensure that data is accurate, secure, accessible, and useful across the organization.

What You’ll Do:

• Design, build, and maintain scalable data infrastructure and data pipelines.
• Own and evolve the architecture supporting operational, analytical, and reporting workloads.
• Develop reliable ingestion, transformation, and data-processing workflows across multiple systems and data sources.
• Maintain and optimize relational and NoSQL databases, including PostgreSQL and MongoDB.
• Establish and improve standards for data quality, validation, lineage, observability, and reliability.
• Monitor data pipelines and infrastructure, investigate failures, and improve resilience and recoverability.
• Design data models and storage strategies that balance performance, scalability, maintainability, and cost.
• Build and maintain integrations between product systems, data platforms, analytics tools, and external services.
• Support analytics and reporting platforms such as Power BI by providing well-structured, reliable datasets.
• Apply appropriate security controls to data systems, including access management, encryption, data isolation, retention, and handling of sensitive information.
• Partner with application and platform engineers to define efficient approaches for generating, storing, querying, and consuming data.
• Improve database and query performance through indexing, schema design, query optimization, and capacity planning.
• Help define engineering standards and best practices for data architecture and data engineering across the organization.
• Participate in technical design reviews and contribute to broader Platform architecture decisions.
• Mentor other engineers and provide technical guidance on database, data pipeline, and data architecture topics.

What We’re Looking For:

• Strong professional software engineering experience, including experience designing and operating production systems.
• Significant experience building and maintaining data pipelines and data infrastructure.
• Strong knowledge of relational databases and SQL, including schema design, indexing, query optimization, and performance troubleshooting.
• Experience with PostgreSQL or similar relational database platforms.
• Experience with document or NoSQL databases such as MongoDB.
• Experience designing data models for both operational and analytical use cases.
• Familiarity with distributed data-processing or big-data technologies such as Apache Spark.
• Experience supporting analytics and business intelligence platforms such as Power BI.
• Experience working with cloud infrastructure and managed data services in AWS, Azure, or similar environments.
• Understanding of data security principles, including authentication, authorization, encryption, data classification, and least-privilege access.
• Experience building observable and reliable data systems, including monitoring, alerting, logging, and failure recovery.
• Strong understanding of software engineering practices including source control, automated testing, CI/CD, code review, and infrastructure as code.
• Ability to communicate technical concepts clearly and collaborate across engineering and non-engineering teams.

Nice to Have:

• Experience with data warehouses, data lakes, or lakehouse architectures.
• Experience with change data capture, event-driven architectures, or streaming data platforms.
• Experience with technologies such as Kafka, Airflow, dbt, Databricks, or equivalent tooling.
• Experience designing data governance, lineage, retention, or lifecycle-management practices.
• Experience managing high-volume transactional or event data.
• Experience with containerized and cloud-native infrastructure.
• Experience supporting data platforms used across multiple products or engineering teams.

What Success Looks Like:

• In this role, you will help establish a dependable data foundation for the organization. Our data pipelines and platforms should be observable, maintainable, secure, and able to scale as our p