Remote job
Data Engineer II
Job details
About this role
Role overview
A data platform engineering team is hiring a Data Engineer II to design and sustain the pipelines and production software that power large-scale analytics, experimentation, and machine-learning workloads. The work blends data engineering with platform engineering, combining disciplined software craftsmanship with pipeline design at petabyte volumes. The role suits someone who enjoys building features end-to-end, working across a broad technology stack, and shipping frequently alongside globally distributed engineers.
Responsibilities
- Design, build, and maintain ETL/ELT data pipelines that move terabyte-scale data through warehouse and lakehouse platforms. - Develop reusable, well-modeled datasets consumed by analytics, data science, CRM, machine learning, and other internal teams. - Own the full lifecycle of pipelines: define service-level objectives, monitor performance, and detect anomalies. - Write production-quality Java and Python across ingestion, event processing, REST services, and internal tooling. - Build and operate streaming and batch systems that power both real-time and analytical workloads. - Collaborate with product, analytics, and data science stakeholders to translate ambiguous needs into reliable solutions.
Requirements
- 4–5+ years of experience in data engineering or general software engineering roles. - Strong, hands-on proficiency with production Java and Python, including CI/CD and code-review discipline. - Experience designing large-scale batch or streaming data systems. - Comfort operating cloud infrastructure, ideally on AWS, with Linux and build-tool fluency. - Ability to communicate clearly with technical and non-technical partners and take ownership independently. - Genuine curiosity and willingness to learn new tools as the stack evolves.
Nice to have
- Familiarity with stream-processing frameworks such as Flink or Spark Streaming. - Experience with task orchestration tools like Apache Airflow or comparable systems. - Exposure to additional technologies such as GraphQL, React, Postgres, or Gradle. - Background designing infrastructure for large-scale data processing in Hive, Snowflake, or NoSQL databases. - Understanding of data governance practices and tooling. - Interest in or experience with machine learning, data science, or generative AI workloads.
Benefits and work setup
- Remote-friendly collaboration with flexible scheduling and trust-based accountability. - Competitive compensation including base salary and an annual bonus. - Health benefits with competitive premiums and an employee assistance program. - Annual tuition assistance for qualifying programs and an annual lifestyle benefit. - Charitable donation matching and a generous employee referral scheme. - Travel-related perks and discounts.