• Lead data migration analyst and data migration efforts • Oversee the preparation of complex data queries; Extraction, Transformation, and Load (ETL), data cleansing • Prepare complex data analysis including trends, links, patterns, and an anomaly analysis • Provide data migration planning, strategy, assessment and analysis support to IT AD and delivery partners • Provide data migration testing and validation support designing and executing comprehensive testing strategies • Provide data migration execution and support to IT AD, business partners, stakeholder management • Provide continuous improvement of data migration activities to IT AD and business partners • Optimize data migration activities to resolve performance concerns • Identify areas for business process improvement and reengineering which will alter the data set and impact data migration

• You're the bridge between raw operational chaos and polished analytics. • Building ETL/ELT pipelines that ingest, transform, and serve data at scale • Designing warehouse schemas (star schemas, fact tables, the whole dimensional modeling thing) • Creating pre-aggregated datasets so dashboards load fast and analysts stay happy • Making sure data flows reliably from source systems → transformations → analytics layer • Partnering with analytics team to understand what data they actually need • Optimizing the infrastructure so it doesn't cost a fortune or fall over • Building data quality checks because garbage in = garbage out

• Design, build, and manage our data warehouse, data storage, and data ingestion solutions. • Implement robust and fault-tolerant systems for data ingestion and processing. • Develop canonical datasets to track key product metrics, including user growth, engagement, and revenue. • Understand and translate business needs into data models to support long-term, scalable, and reliable data pipelines • Enhance and maintain the Data Infrastructure using best practices and latest features to ensure high data quality. • Define and manage SLA’s for data sets and processes running in production • Continuously improve our data infrastructure and empower teams with the best data tooling and systems. • Build strong cross-functional partnerships with Data Analysts, Product Managers, and Software Engineers to understand data needs and deliver on those needs. • Participate in data architecture and engineering decisions, leveraging your strong experience and knowledge. • Build lineage and auditability into data pipelines • Be part of a data engineering team that is also responsible for the reliability of the data systems that are built and be available to respond to critical incidents as needed • Ensure the security, integrity, and compliance of data in accordance with industry and company standards.

• Design, build, and operate robust, fault-tolerant, and observable data pipelines using Airflow and modern ELT best practices • Architect, enhance and improve data ingestion, AWS data infrastructure, including Redshift, S3 and monitoring • Partner with Analytics, Product, Finance, Marketing, and Content teams to design canonical, analytics-ready datasets that power key metrics such as growth, engagement, retention, and revenue • Define, implement, and enforce SLAs, data quality checks, observability, and alerting for production data systems. Take shared ownership of data platform reliability, participating in on-call rotations and driving root-cause fixes for incidents • Contribute to design reviews, raising engineering quality, and sharing best practices • Evaluate and introduce data tooling that improves reliability, developer productivity, and analytics velocity • Collaborate deeply with cross functional teams to align event design, source systems, and data contracts