Senior Data Engineer

Job Description The Square Banking team is building a suite of new financial products for Square sellers. We offer business checking accounts, savings accounts, credit card, and loans to help our sellers manage their business cash flow. Investing in a Financial Data Mesh Platform is not just about managing data; it’s about unleashing the full potential of our organization’s most valuable asset. It’s a critical strategic move that not only empowers us to use the distinctive value of data but also extends its positive impact to our customers, our Sellers, and users of the Banking platform.As an Engineer focused on Data for Square Banking, you will help us build our own Square Banking Financial Data Mesh Platform, using real-time Big Data technologies and Medallion architecture. You will work directly with product, engineering, data science and machine learning teams to understand their use-case, develop reliable, trusted datasets that accelerate the decision-making process of important products.Qualifications 8 years as a data engineer or software engineer, with a focus on large-scale data processing and analyticsYou’ve spent 4 years as a data engineer building core datasetsYou are passionate about analytics use cases, data models and solving complex data problemsYou have hands-on experience shipping scalable data solutions in the cloud (e.g AWS, GCP, Azure), across multiple data stores (e.g Databricks, Snowflake, Redshift, Hive, SQL / NoSQL, columnar storage formats) and methodologies (e.g dimensional modeling, data marts, star / snowflake schemas)You have hands-on experience with highly scalable and reliable data pipelines using BigData (e.g Airflow, DBT, Spark, Hive, Parquet / ORC, Protobuf / Thrift, etc)Optimized and tuned data pipelines to enhance overall system performance, reliability, and scalabilityKnowledge of programming languages (e.g. Go, Ruby, Java, Python)Willingness to participate in professional development activities to stay current on industry knowledge and passion for trying new thingsResponsibilities You will work directly with product, engineering, data science and machine learning teams to understand their use-case, develop reliable, trusted datasets that accelerate the decision-making process of important productsYou’ll design large-scale, distributed data processing systems and pipelines to ensure efficient and reliable data ingestion, storage, transformation, and analysisPromote high-quality software engineering practices towards building data infrastructure and pipelines at scaleYou’ll build core datasets to serve as unique sources of truth for product and departments (product, marketing, sales, finance, customer experience, data science, business operations, IT, engineering)You’ll partner with data scientists and other cross-functional partners to understand their needs and build pipelines to scaleIdentify and address data quality and integrity issues through data validation, cleansing, and data modeling techniquesYou’ll implement automated workflows that lower manual / operational cost for team members, define and uphold SLAs for timely delivery of data, move us closer to democratizing data and a self-serve model (query exploration, dashboards, data catalog, data discovery)Learn about Big Data architecture via technologies such as AWS, DataBricks and KafkaStay up to date with emerging technologies, best practices, and industry trends in data engineering and software developmentMentor and provide guidance to junior data engineers fostering inclusivity and growthWork remotely with a team of distributed colleaguesReport to the Engineering Manager of Banking - Data Engineering#J-18808-Ljbffr