Senior Data Engineer

Arena Club•Los Angeles, CA

3h•$130,000 - $170,000

About The Position

We are seeking a Senior Data Engineer to help strengthen Arena Club’s strategic decision-making, enhance operational performance, and integrate data across the company to unlock deeper insights into customer behavior and market performance. As a key individual contributor, you’ll focus on building and maintaining reliable data pipelines, improving data quality, and ensuring data is well-instrumented, accessible, and structured to support meaningful analysis. You will work with existing tools and systems, including Mixpanel and AWS-based data infrastructure, partnering closely with engineering and business teams across product, operations, and the marketplace. This is a hands-on role for someone who enjoys owning execution, operating in evolving data environments, and incrementally improving how data is collected, processed, and used to drive better business decisions.

Requirements

5+ years in data engineering with production pipeline ownership (not just analytics or BI)
Deep AWS experience: Glue (both Python Shell and Spark ETL), Redshift, S3, IAM, EventBridge, Lambda, AppFlow
Strong SQL: complex joins, window functions, MERGE/UPSERT patterns, Redshift-specific optimization (sort keys, dist keys, VACUUM/ANALYZE)
Python fluency: boto3, data processing libraries, writing production Glue scripts (not just notebooks)
Dimensional modeling: star schemas, fact/dimension design, SCD Type 1 and Type 2 implementation
dbt: hands-on experience building and maintaining staging, intermediate, and mart models with tests and documentation
Data warehouse operations: schema migration, incremental loads, backfill strategies, monitoring, and alerting
Hands-on experience using AI tools (Claude or Cursor preferred; other agentic tools welcome) to ship code, build agents, and automate workflows

Nice To Haves

Redshift Spectrum: experience with external schemas, Parquet/Hive partitioning, and unified hot/cold querying
CDC / streaming: Postgres WAL, Debezium, EventBridge, or similar change data capture pipelines
Data Mesh concepts: domain-oriented ownership, data-as-a-product thinking, federated governance
AppFlow & SaaS integrations: configuring and troubleshooting managed connectors for Stripe, Zendesk, Mixpanel, etc.
Cost optimization: right-sizing Glue jobs (Python Shell vs. Spark), Redshift concurrency scaling, S3 lifecycle policies
Vendor distribution: building outbound API sync jobs with rate limiting, SFTP transfers, webhook delivery
Familiarity with marketplace or e-commerce data (orders, payments, attribution, promo codes)
Experience with Mixpanel, Customer.io, or Singular data exports and event schemas
Prior experience migrating from monolithic ETL to medallion or lakehouse architectures
Exposure to data governance tooling: data catalogs, lineage tracking, quality frameworks (e.g., Great Expectations, dbt tests)

Responsibilities

Maintain and optimize inbound and outbound ETL pipelines built on AWS Glue (Python Shell & Spark ETL)
Manage Redshift cluster performance across various schemas
Own integrations with SaaS data sources via AppFlow and direct connectors
Operate outbound distribution pipelines to external vendors
Manage infrastructure, alerting, and migration state tracking
Lead the migration from ad-hoc SQL scripts to a Bronze/Silver/Gold medallion architecture with dbt as the transformation layer
Design and implement dimensional models, i.e., fact tables and dimensions
Build the Silver staging layer
Architect the real-time CDC pipeline
Implement data contracts and governance at the Silver layer to insulate downstream consumers from source changes
Implement a hot/cold storage strategy via Redshift Spectrum
Build the Unified Access Layer
Design and automate Glue jobs
Configure S3 lifecycle policies for progressive cost reduction