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    Staff Engineer, Software Engineering and Transformation - Washington DC, United States - Social Finance Ltd

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    Description
    Shape a brighter financial future with us.
    Together with our members, we're changing the way people think about and interact with personal finance.

    We're a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals.

    The industry is going through an unprecedented transformation, and we're at the forefront. Join us to invest in yourself, your career, and the financial world.
    SoFi runs on data We are seeking a highly motivated Staff Software Engineer (Contract)to join our Data Platform team.

    As a Staff Software Engineer (Contract), you will work alongside our experienced team of data engineers and product managers to develop and maintain our cutting-edge data handling platform using Snowflake, dbt, Sagemaker, and Airflow.

    In this role you will be contributing to the long-term success of SoFi's data vision by building out distributed systems and scalable data platforms.

    As a Staff engineer on the Data Platform team at SoFi, you'll be tasked with building critical components and features.

    The ideal candidate has a strong software engineering background and problem-solving ability along with cloud computing (AWS) and data engineering skill set with prior experience on technologies such as Snowflake, Airflow, dbt, Kafka, Spark, Dask, Python, and Tableau.


    Note:
    Due to the temporary nature of this role, we're unable to provide sponsorship at this time.

    Lead architectural design sessions for the modern data stack, emphasizing solutions that seamlessly integrate Snowflake, Databricks, Airflow, dbt, Great Expectations, and AWS data services.

    Drive the development of advanced features within the data platform, ensuring modular, efficient, and scalable code structures optimized for the aforementioned stack.

    Spearhead rigorous code review processes, underscoring best practices, efficiency, and optimal use of Snowflake's unique capabilities and AWS data services.

    Collaborate closely with product and data governance leadership to comprehend intricate user needs and translate them into technical designs that leverage the power of Snowflake, Airflow, dbt, Terraform, DMS, Kafka and Great Expectations.

    Foster and facilitate internal technical sessions, exploring nuances of AWS data services like DMS, MSK (Kafka) , and S3, and sharing best practices for integration with the broader data stack.

    Stay at the forefront of advancements in data engineering methodologies, particularly as they pertain to Snowflake, Databricks, and other modern data tools.

    Engineer sophisticated data pipelines using dbt, Airflow, and Snowflake, with special emphasis on performance optimization and data integrity using Great Expectations.

    Architect robust data governance systems, ensuring strict data integrity, compliance, and robust metadata management within the Snowflake and AWS ecosystems.

    Design and implement advanced data anomaly detection systems within the Snowflake-dbt paradigm, utilizing Great Expectations for data quality checks.

    Leverage Python and SQL scripting proficiencies for intricate data operations, custom ETL/ELT processes, and sophisticated data transformations across the platform.

    Mentor technical team members in best practices for Snowflake, Databricks, Airflow, dbt, and AWS data services, promoting a culture of technical distinction and innovation.

    Advanced degree in Computer Science, Engineering, or an allied technical discipline.

    5+ years in a pivotal Software/Data Engineering role, with deep exposure to modern data stacks, particularly Snowflake, Airflow, dbt, and AWS data services.

    Profound hands-on experience with Snowflake's data warehousing solutions, Databricks' analytics platform, and the orchestration capabilities of Airflow.

    Expertise in establishing data quality assurance frameworks, particularly using Great Expectations, and crafting data governance strategies tailored to modern data stacks.

    Proven skills in metadata management, distributed data architecture, and optimizing dbt models and transformations.

    Mastery in Python and SQL for complex operations within Snowflake, and AWS services like DMS, MSK (KAfka) ,Kinesis, and S3.

    Demonstrable problem-solving capabilities, especially within the context of the modern data stack.
    Exceptional technical communication skills, adept at liaising with both technical peers and diverse stakeholders within a data-driven organization.
    Experience working on financial regulatory projects.

    SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.

    SoFi is committed to embracing diversity. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email
    Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.

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