[Remote] Senior Data Engineer

Note: The job is a remote job and is open to candidates in USA. The Motley Fool is a purpose-driven financial services company focused on making the world smarter, happier, and richer. They are seeking a Senior Data Engineer to design and manage the data infrastructure that powers investment operations, ensuring reliable and timely data for stakeholders.ResponsibilitiesDesign, build, and maintain robust ETL/ELT pipelines using Apache Airflow (MWAA). Author DAGs that handle complex dependencies across external data vendors, internal models, and downstream consumersIngest data from diverse sources including SFTP feeds, REST APIs, flat files, and third-party financial data providers. Normalize and conform data into a consistent analytical modelBuild 'circuit breakers' into pipelines: automated data quality checks that halt downstream processing and alert the team via CloudWatch and Slack when anomalies are detectedImplement AWS Lambda functions for lightweight, event-driven tasks such as triggering ingestion when files land in S3 or validating data payloads before loadingMaintain and document the data catalog so institutional knowledge lives in the system, not in your headServe as the subject-matter expert for Snowflake. Design schemas, manage data loading via Stages and Snowpipe, and implement role-based access controlsWrite advanced analytical SQL: window functions, CTEs, recursive queries, pivots; to support investment reporting, performance attribution, and ad-hoc analysisProfile and optimize slow-running queries. Leverage clustering keys, micro-partition pruning, materialized views, and result caching to minimize compute cost and maximize performanceDefine and deploy cloud resources using Terraform or AWS CDK. Treat infrastructure as software with version control, peer review, and automated testingHelp design and maintain CI/CD workflows with GitHub Actions for automated testing, linting, and deployment of data pipelines, infrastructure, and application codePartner with investment and business teams to translate questions into data models, dashboards, and reports that drive strategic decisions using TableauDesign and build automated pipelines that pull data from source systems and render it into production-ready marketing outputs: one-pagers, pitch decks, email campaigns, and social contentBe a resource for software engineers to build an AI layer on top of existing data infrastructure, enabling LLMs to securely query fund performance data via APIs and answer natural-language questions for internal stakeholdersSkills5+ years of professional Python developmentComfortable with object-oriented design, data manipulation libraries (pandas, NumPy)Familiarity with financial research data vendors and feed/API products such as CapIQ Xpressfeed, FactSet, Bloomberg, Thomson Reuters/Refinitiv/LSEG, Russell or MSCIFamiliarity with financial business data and feed/API products from Broadridge, Morningstar and custodian banks and fund administratorsProven experience designing and operating ETL/ELT pipelinesDeep expertise in Snowflake architecture (clustering keys, micro-partitions, Snowpipe, Stages)Able to write complex analytical SQL, window functions, CTEs, recursive queries, and optimize them for cost and performanceHands-on experience with AWS CDK or TerraformExposure to LLM integration patterns: markdown files and prompt engineeringWorking knowledge of the AWS ecosystem: Lambda, ECS Fargate, Step Functions, S3, EventBridge, CloudWatch, and RDSExperience with data visualization tools (Tableau, Streamlit, or similar) for self-service analyticsBackground in data governance, data cataloging, or data lineage toolingDemonstrated experience maintaining CI/CD pipelines for automated testing and deployment of data engineering and application code using Github actions and TerraformExperience profiling and optimizing queries across both OLAP (Snowflake) and OLTP (PostgreSQL/Aurora) systemsFamiliarity with EXPLAIN plans, indexing strategies, and database-level performance tuningPractical experience building, evaluating, and deploying ML modelsFamiliarity with common frameworks (scikit-learn, XGBoost) and an understanding of when and how to apply ML to business problemsCompany OverviewThe Motley Fool is a multimedia financial services company providing websites, books, newspaper columns, TV appearances, and newsletters. It was founded in 1993, and is headquartered in Alexandria, Virginia, USA, with a workforce of 201-500 employees. Its website is http://fool.com.