Analytics Engineer

One of our top media and entertainment clients is seeking an Analytics Engineer to support subscription and streaming analytics during a critical growth period leading into the World Cup. This role sits at the intersection of data engineering, analytics, and production support, partnering closely with business, marketing, engineering, and third-party teams.

The Analytics Engineer will build and support data pipelines, integrate internal and external data sources, troubleshoot production data issues, and enable rapid business insights.

Responsibilities include working in Snowflake, ingesting file-based data primarily CSVs, managing data flows in AWS S3, making minor updates to Tableau dashboards, and delivering fast, reliable analysis during high-demand events.

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5+ years of experience in analytics engineering, data engineering, or advanced analytics roles supporting production data systems

Strong SQL expertise in Snowflake (or similar cloud data warehouse), including writing complex joins, aggregations, CTEs, and CASE logic; debugging data issues; and optimizing queries for production use

Proven experience using SQL for data transformations, analytics modeling, and ad-hoc analysis within the warehouse

Hands-on experience troubleshooting production data issues, such as missing, duplicated, or mismatched data across pipelines and reports

Cloud experience, preferably AWS, with hands-on use of S3 for ingesting, validating, and processing data files

Experience supporting file-based data integrations (CSV and structured flat files) and API-based data integrations

Python proficiency for data processing, automation, or pipeline support (intermediate level acceptable)

Experience working in business-critical production environments with time-sensitive analytics and reporting needs Experience in media, entertainment, streaming, or subscription/DTC environments

Familiarity with third-party platforms such as Stripe, Braze, or subscription/commerce systems

Familiarity with BI and visualization tools such as Tableau, Power BI, Looker, or Sigma (read/support level)

Experience working in high-traffic or event-driven environments (e.g., product launches, live events, seasonal spikes)