Senior Data Engineer

Get to Know Our Team:
Our Data Engineering team builds the data backbone for a large-scale consumer platform. We industrialize data feeds, build and run ETL pipelines, and maintain the data warehouse layers that turn raw operational data into insight — in direct contact with product, business, and analytics stakeholders who depend on us daily.

Get to Know the Role:
As a Senior Data Engineer, you'll shape how we get data from source to decision. You'll build and industrialize data pipelines across our layered data architecture, be the engineering point of contact for business needs, and help decide which technologies best serve the data our stakeholders depend on — reporting, dashboards, product analytics, and downstream data science use cases.

The Critical Tasks You Will Perform:

1. Build, maintain, and support production data pipelines (ETL, streaming, batch) using Python and SQL, leveraging AI tooling to accelerate delivery

2. Act as the engineering point of contact for business stakeholders, gathering and assessing their data needs

3. Ensure data architecture meets business and reporting requirements, including SLA commitments

4. Recommend ways to deliver quality data more efficiently and identify opportunities to add value

5. Run multiple concurrent pipeline projects and migrations from scoping through delivery

6. Work closely with backend engineers on source-system migrations — re-pointing and validating data pipelines during active platform cutovers — to ensure no data loss or SLA breach

Why Join Us:
You'll own the pipelines behind decision-making for a large-scale consumer platform — with direct influence over the technology choices, architecture, and data quality bar the business relies on.

Qualifications:
What Essential Skills You Will Need

1. 4+ years of experience in data engineering, building and operating production data pipelines at scale

2. Strong hands-on Python and SQL skills

3. Knowledge of Big Data technologies such as Scala, PySpark, Presto, and Airflow

4. Solid understanding of ETL and layered data warehousing patterns

5. Fluency in written and spoken English

6. Ability to analyze, synthesize, and simplify complex data problems for varied audiences

7. Demonstrated ability to work directly with business stakeholders to scope and deliver data solutions

8. Strong communication skills — able to explain technical tradeoffs to non-technical stakeholders (analysts, product managers, business leads)

9. Proven ability to prioritize and manage multiple concurrent projects, meeting deadlines without compromising data quality

10. Experience tracing data lineage and validating pipelines through backend/platform-driven migrations

11. Experience with streaming platforms (e.g., Kafka and Flink)

Good to Have:

1. Backend programming experience (e.g., Golang, Java)

2. Knowledge of descriptive statistics and hypothesis testing

3. Experience with BI/visualization tools (e.g., Tableau, Power BI, Superset)

4. Exposure to data governance practices: data quality, PII handling, data protection/purge

5. Background in a large-scale marketplace or consumer platform data domain

Why Join Us:
You'll own the pipelines behind decision-making for a large-scale consumer platform — with direct influence over the technology choices, architecture, and data quality bar the business relies on