Data Engineer II

Job Description

Responsibilities

Data Engineering & Data Products, ETLs

• Design, build, and maintain robust ETL/ELT data pipelines that process terabyte-scale data across Snowflake, BigQuery, Hive, and other platforms.
• Develop scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization.
• Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection.
• Ensure enterprise data integrity, validation, documentation, and governance.

Platform & Software Engineering

• Write production Java and Python code across our evolving platform stack — from data ingestion and event processing to REST services and internal tooling.
• Build and maintain streaming and batch processing systems (Flink, Spark, Kafka) that power real-time and analytical workloads.
• Take responsibility for all aspects of software engineering: design, implementation, QA, and maintenance, with a CI/CD mindset (most engineers release to production every few days).
• Operate on and improve cloud infrastructure on AWS, with familiarity with Gradle, Linux, and related tooling.

Quality, Collaboration & Ownership

• Take on projects with independence and a mandate to leave things better than you found them.
• Be integral to code quality on your team through leadership in design and code review.
• Collaborate closely with Product, Design, Analytics, and Data Science teams to define specifications and deliver high-quality solutions.
• Communicate effectively with both technical and business stakeholders; translate complex data problems into clear solutions.
• Work alongside engineering groups located around the world in a fast-paced, dynamic environment.

Skills & Experience

• 4–5+ years of data engineering or general software development experience in a commercial setting.
• Strong hands-on proficiency in both Java and Python for production systems.
• Demonstrated experience designing and implementing complex ETL/ELT processes from concept to production.
• Proficiency in SQL and data exploration across large, complex datasets.
• Experience with big data technologies (Hadoop, Hive, BigQuery, Snowflake) and working with terabyte-scale or larger datasets.
• Solid foundation in data structures, algorithms, and object-oriented design.
• Professional experience building REST services and working with event queue systems.
• Familiarity with Linux and cloud infrastructure design on AWS or equivalent cloud providers.
• Systems performance and tuning experience, with an understanding of how architecture impacts scalability.
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• Strong analytical skills; desire to write clean, correct, and efficient code.
• Self-paced, organized, and detail-oriented with a strong sense of ownership, urgency, and pride in your work.
• Ability to break down complex problems into simple, pragmatic solutions.
• Strong interpersonal skills, intense curiosity, and enthusiasm for solving difficult problems.
• Willingness and ability to take on new technologies as our stack evolves.

Nice to Have

• Experience with stream processing frameworks such as Flink or Spark Streaming.
• Experience with task orchestration tools such as Apache Airflow or similar systems.
• Familiarity with additional technologies: GraphQL, React, HTML5, JavaScript, CSS, Postgres, Gradle, BERT.
• Experience working with and designing infrastructures for large-scale data processing (Hive, Snowflake, NoSQL databases).
• Experience with data governance practices and tooling.
• Exposure to and/or interest in machine learning, data science, or GenAI to help solve engineering challenges innovatively.
• Experience developing scalable code for high-volume, low-latency systems.

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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