Big Data Engineer

TP-Link Systems • Irvine, CA

1d

About The Position

TP-Link Systems Inc. is seeking a Big Data Engineer to join their team. This role involves owning components of the data platform end-to-end, including design, development, and maintenance of data pipelines, tables, quality checks, monitoring, and recovery. The engineer will work with technologies like EMR (Spark), Airflow, DataX/CDC, and OLAP engines such as StarRocks. The position requires close collaboration with analysts and business stakeholders to translate requirements into usable data models and datasets. The company is a global provider of networking devices and smart home products, committed to innovation and delivering reliable connectivity worldwide.

Requirements

• Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
• 2+ years of hands-on data development in a production environment — scheduled pipelines with real downstream consumers.
• Experience owning a pipeline or component in production: you were the person accountable for it, including when it broke.
• Strong SQL: window functions, complex multi-table joins, incremental and idempotent writes; able to read an execution plan and diagnose data skew or slow queries.
• Production-grade Python: maintainable, testable ETL and tooling code (PySpark / pandas / boto3) with proper error handling and logging.
• Hands-on with Spark on EMR, or equivalent Hadoop / Hive experience, including partitioning, shuffle, and memory tuning.
• Production experience with Airflow: DAG design, dependencies, retries, idempotent reruns, backfills, and SLA alerting.
• Experience with a data ingestion or CDC tool in production (DataX, Sqoop, Debezium, or similar): extracting from OLTP sources, incremental sync, and handling upstream schema changes.
• Experience with an OLAP engine — StarRocks, Doris, or ClickHouse: table models, partitioning and bucketing, materialized views, and query tuning.
• Solid grasp of data warehouse modeling: dimensional modeling, slowly changing dimensions, and layering conventions.
• Comfortable on AWS (S3 with Parquet / ORC and sensible partitioning, IAM basics, day-to-day EMR operations), Linux, and Git.
• Comfortable picking up new tools as the platform evolves — we'd rather hire someone who learns a new engine quickly than someone who has only ever used ours.
• Effective use of AI to solve data problems — using it to move faster on SQL, debugging, and unfamiliar schemas, with the judgment to catch output that looks right but isn't.

Nice To Haves

• AWS cost optimization: EMR instance sizing and Spot strategy, S3 lifecycle policies, StarRocks vs. Athena trade-offs.
• Lakehouse table formats: Iceberg, Hudi, or Delta.
• Streaming: Kafka with Flink or Spark Structured Streaming.
• dbt, Glue Data Catalog, data lineage, or a data quality framework.
• QuickSight dataset, SPICE, and row-level permission design.

Responsibilities

• Own a component of the data platform end to end — its pipelines, tables, quality checks, monitoring, and recovery.
• Design and build ETL on EMR (Spark) and Airflow, and data ingestion from OLTP sources via DataX / CDC, including incremental sync and upstream schema changes.
• Model the data for your area: dimensional models and layering (ODS / DWD / DWS / ADS) that serve real analytical use cases.
• Own data quality for your component — write the checks and freshness monitoring, and resolve issues before they reach downstream users.
• Tune runtime and infrastructure cost for the jobs you own, and choose the right engine for a workload (StarRocks serving vs. batch on EMR).
• Build components other engineers can reuse, and automate work that would otherwise repeat.
• Work directly with analysts and business stakeholders to turn requirements into models and datasets that actually get used.

Benefits

• Salary range: TBD
• Free snacks and drinks
• Fully paid medical, dental, and vision insurance (partial coverage for dependents)
• Contributions to 401K funds
• Bi-annual reviews, and annual pay increases
• Health and wellness benefits, including free gym membership
• Quarterly team-building events

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level