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TP-Link Systems

Networking and smart home technology

Big Data Engineer

Data EngineeringPosted on Nov 10
Full-timeIrvine, CA, USAIn-person

About the Job

Requirements

  • 2–4 years of hands-on data development in a production environment, responsible for scheduled pipelines with downstream consumers, including troubleshooting failures.
  • Strong SQL skills, including window functions, complex multi-table joins, incremental loads, and query performance analysis.
  • Python for production ETL and tooling, including PySpark, pandas, and boto3.
  • Hands-on experience with Spark on a cloud platform such as AWS EMR, Databricks, or Glue.
  • Production experience with a scheduler; Airflow is preferred, including DAG design, dependencies, retries, and safe reruns.
  • Working understanding of dimensional modeling, including fact and dimension tables, star schema, and warehouse layering.
  • Comfort working with AWS (S3 with Parquet or ORC), Linux, and Git, and ability to pick up new tools as the platform evolves.
  • Effective use of AI to solve data problems, including SQL, debugging, and unfamiliar schemas, with judgment to validate outputs.
  • Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.

Responsibilities

  • Build, run, and own ETL pipelines on EMR (Spark) orchestrated in Airflow, including monitoring, alerting, and recovery.
  • Write SQL and Python for data ingestion, transformation, and datasets used by analysts and dashboards.
  • Own data quality for built solutions by running checks before release, adding missing checks, and confirming results are correct.
  • Build and extend data models, including fact and dimension tables, following team layering conventions.
  • Monitor job runtime and cost, and raise slow or expensive jobs for attention.
  • Use and extend shared patterns and templates, and automate or make repeatable recurring work.
  • Work with analysts and business stakeholders to turn requests into useful datasets.

Desired Qualifications

  • Data ingestion or change data capture tooling such as DataX, Sqoop, Debezium, or Fivetran.
  • An OLAP or MPP engine such as StarRocks, Doris, ClickHouse, or Redshift.
  • Spark performance work, including partitioning, shuffle, skew, and memory tuning.
  • AWS cost optimization, including EMR instance sizing, Spot strategy, and S3 lifecycle policies.
  • Lakehouse formats such as Iceberg, Hudi, or Delta; streaming tools such as Kafka or Flink; dbt; or a data quality framework.
  • QuickSight or another business intelligence tool, including dataset and permission design.
  • Self-directed learning demonstrated through a project, open-source contribution, or a tool independently learned and put to practical use.

About the Company

TP-Link Systems

Networking and smart home technology

TP-Link Systems is the U.S. organization for TP-Link networking and connected-home products. Its portfolio includes Wi-Fi routers and mesh systems, switches, access points, cameras, smart-home devices, and business networking equipment. The company serves consumers, small businesses, enterprises, and service providers through retail and channel partners. TP-Link participates in networking, consumer electronics, and connected devices, with engineering, product, channel, sales, support, and operations teams bringing integrated hardware, software, cloud services, and security updates to market.

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