Senior Data Engineer

About the role: We're partnering with an innovative video streaming company that delivers content to millions of viewers across live and on-demand platforms. As they continue to scale globally, they're looking for a Senior Data Engineer to join the team building out their modern, cloud-based data platform on AWS. This role sits within the Data Engineering function, working closely with the Senior Data Architect and Analytics teams to build the pipelines, models, and infrastructure that power viewer analytics, content performance reporting, and operational insight across the business. This is a foundational hire on the data team, with the platform being built to support future AI/ML and personalization use cases down the line, but the immediate focus is rock-solid data pipelines, modelling, and infrastructure. What You'll Do: • Design, build, and maintain scalable batch and streaming data pipelines to ingest data from internal platforms (playback, content, subscription, billing, advertising) and third-party sources. • Develop and maintain data models in Snowflake, following architecture and governance standards set by the Data Architecture team. • Write clean, efficient, well-tested SQL and Python for transformation, orchestration, and data quality checks. • Build and maintain ELT pipelines using dbt (or similar), ensuring transformations are modular, documented, and version-controlled. • Orchestrate and monitor pipelines using tools such as Airflow, Dagster, or AWS-native services (Step Functions, Glue). • Work with AWS services (S3, Glue, Lambda, Kinesis/MSK) to support data ingestion, storage, and processing at scale. • Partner with Analytics, Product, and Platform teams to understand data needs and deliver reliable, well-documented data sets. • Implement data quality checks, testing frameworks, and monitoring/alerting to catch issues before they hit downstream consumers. • Contribute to data documentation, cataloguing, and lineage as part of the wider data governance effort. • Support the migration of legacy data sources and processes onto the modern cloud data platform. • Participate in code reviews, sprint planning, and continuous improvement of data engineering practices and standards. What We're Looking For: • 3-5+ years of experience as a Data Engineer, ideally supporting analytics, product, or reporting functions at scale. • Strong hands-on experience with Snowflake (or a comparable cloud data warehouse), including performance tuning, warehouse management, and cost optimization. • Strong SQL skills, including experience with dimensional modelling (star/snowflake schemas) and building analytics-ready data sets. • Solid Python skills for data pipeline development, scripting, and automation. • Experience building ELT/ETL pipelines using dbt or equivalent transformation frameworks. • Experience with pipeline orchestration tools (Airflow, Dagster, Prefect, or AWS Step Functions/Glue). • Working knowledge of core AWS data services: S3, Glue, Lambda; exposure to streaming tools such as Kinesis or Kafka/MSK is a plus. • Understanding of data modelling best practices, version control (Git), and CI/CD for data pipelines. • Comfortable working with large, high-volume datasets (viewer/event-level data, clickstream, or similar high-cardinality data is a bonus). • Strong attention to data quality, testing, and documentation. • Good communication skills and comfort working directly with analytics and business stakeholders to traanslate requirements into pipelines. Nice to Have: • Experience within video streaming, OTT, broadcast, media, or ad-tech. • Experience with event/streaming data (viewer engagement, playback events, ad impressions). • Familiarity with Apache Spark, Kafka, or Delta Lake/Iceberg table formats. • Exposure to Infrastructure as Code (Terraform or CloudFormation). • Experience with BI/analytics tools such as Looker, Tableau, or Power BI (from a data-modelling perspective).