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    Data Engineer - San Francisco, United States - FocusKPI Inc.

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    Description

    Job Description

    Job DescriptionFocusKPI is looking for a Data Engineer to join one of our client's team and to support them. As a member of the Data Engineering, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity in our client's product offerings.

    Work Location: Remote - anywhere in US
    Duration: 6 months
    Pay Range: $60+/hr

    Responsibilities:
    • Collaborating with business teams on the design, deployment and continuous improvement of the scalable data platform that ingests, stores, and aggregates various datasets, including data pipelines, platforms, and warehouses, and surfacing data to both internal and customer-facing applications.
    • Being a domain expert on data modeling, data pipelines, data quality and data warehousing.
    • Designing, building and maintaining data ETL/ELT pipelines to source and aggregate the required data for various data analyses and reporting needs, as well as to continually improve the operations, monitoring and performance of the data warehouse.
    • Developing integrations with third party systems to source, qualify and ingest various datasets.
    • Enabling data analytics and visualization tools to extract valuable insights from the data to enable data-driven decisions.
    • Working closely across groups, such as the product, engineering, data science, and external partners for data modeling, general management of data life cycle, data governance and processes for meeting regulatory and legal requirements.
    • You will aspire to our four core values: Multi stakeholder - you have dedication and commitment to our customers, shareholders, employees and families and local communities. Mindful - you seek to be respectful, an active listener and to pay attention to detail. Driven by Excellence - you are driven by our mission and our passion for customer success which means you relentlessly pursue excellence, that you do not tolerate mediocrity and you work intensely to achieve your goals. High Integrity - you seek open and honest communication, and you hold yourself to very high moral and ethical standards. You reject manipulation, dishonesty and intolerance.
    Qualifications:
    • 4+ years of professional data engineering experience.
    • Proficient in one or more programming languages (Java, Scala, Python).
    • Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Data bricks, etc.
    • Experience in SQL and NoSQL, such as MySQL, PostgreSQL, Cassandra, HBase, Redis, DynamoDB, Neo4j, etc.
    • Experience with workflow orchestration management engines such as Airflow, Dagster, DBT, etc
    • Experience with Cloud Services (AWS, Google Cloud, Microsoft Azure, etc).
    • Experience in building scalable infrastructure to support batch, micro-batch or stream data processing for large volumes of data.
    • Experience with blockchain protocols.
    • Experience in data provenance and governance.
    • Internal knowledge of open source or related big data technologies.
    • Ability to tackle complex and ambiguous problems.
    • Self-starter who takes ownership, gets results, and enjoys moving at a fast pace.
    • Excellent communication skills, able to collaborate with across remote teams, share ideas and present concepts effectively.

    Thank you

    FocusKPI Hiring Team

    Founded in 2010, FocusKPI, Inc. (FocusKPI) is a data science and technology firm specializing in predictive analytics practice and methodologies. FocusKPI is a US company headquartered in Silicon Valley, California, with an East Coast office in Boston, Massachusetts.

    NOTICE: Please be aware of fraudulent emails regarding job postings, job offers and fake checks. FocusKPI's recruiting team will strictly reach out via email domain. If you have received fraudulent emails now or in the past, please report it to .
    The domain is fraudulent and not related to FocusKPI. Please do not not reply or communicate to anyone with

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