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    Data Engineer - Detroit, United States - OneMagnify

    OneMagnify
    OneMagnify Detroit, United States

    3 weeks ago

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    Description

    About You:

    You are an experienced cloud engineer with advanced technical skills and great attention to detail. You enjoy turning data into business solutions. You are a troubleshooter and passionate about what you do. You enjoy building relationships with data product owners and developing a complete understanding of data infrastructure.

    • Resourceful and relentless: independently capable of seeking information, corralling resources, data wrangling (query, join, manipulate, automate), and delivering results in challenging situations
    • Collaboration and Teamwork: works with others to deliver results, contributing to the team and prioritizing group needs over individual needs
    • Problem Solving: uses an organized and logical approach to find solutions to complex problems. Looks beyond the obvious to uncover the root cause of problems
    • Open Communication: clearly conveys thoughts, both written and verbally, listening attentively and asking questions for clarification and understanding
    • Comfortable in the Spotlight: able to interact with clients regularly and effectively and be seen as a subject matter expert.
    What you'll do:
    • Leverage Google Cloud Platform tools such as BigQuery, Cloud Dataflow, Cloud Dataprep, and Cloud Pub/Sub to deliver top-tier services to our clients' customers and to advance the Data & Analytics Road Map.
    • Perform end-to-end big data ETLs and analytics using SQL, Python and GCP tools to meet critical business needs and craft fault-tolerant, scalable code ready for production.
    • Create and evaluate comprehensive data models, including entity-relationship diagrams and dimensional data models. Utilize GCP's data services to implement ETL processes, business rules, data management, governance, lineage, metadata, and reporting solutions to develop complete data product solutions.
    • Manipulate large data sets using SQL & Python (pySpark/Beam) to understand patterns in the data. Perform data profiling using various tools to learn the shape of the data to help inform data quality checks and/or curation rules that need to be developed.
    • Partner with clients and data scientists in interpreting data and remediating issues when required.
    • Collaborate with data owners and stewards to enforce, maintain, and enhance data governance, quality, security, and privacy standards using GCP's robust security and compliance capabilities, including Cloud IAM and Data Catalog for metadata management.
    • Prepare technical specifications for data ingestion and transformation processes using services like Cloud Dataflow and Cloud Dataprep. Collaborate with data architects to construct efficient data models for data consumption, optimized for performance and cost in Google Cloud.
    • Advocate for the development and adherence to standards and best practices within the Data Engineering team, including the use of documentation templates, agile development methodologies, and GCP's best practices for security, data governance, and efficient cloud resource utilization.
    What you'll need:
    • Bachelor's degree in computer science, Engineering, Mathematics, or another relevant discipline.
    • 2+ years of experience in architecting and scaling big data pipelines and analytical solutions on GCP or AWS, utilizing open-source libraries and frameworks such as Apache Spark, Apache Beam, and Apache Flink for data processing.
    • Proficiency in ETL (Extract, Transform, Load) processes across a variety of database technologies including RDBMS (e.g., MS SQL Server, Oracle, MySQL, PostgreSQL), MPP (e.g., Google BigQuery, AWS Redshift, Teradata, Snowflake), and NoSQL databases (e.g., MongoDB, AWS DynamoDB, Cassandra), demonstrating an in-depth understanding of data storage, retrieval, and management practices.
    • Advanced SQL skills for resource optimization and managing extensive datasets in Google BigQuery and Snowflake.
    • Highly skilled in Python (or Scala) for developing petabyte-scale data processing jobs on cloud services like AWS EMR, GCP Dataproc/Dataflow, or on-premise setups, incorporating technologies like Apache Spark and Apache Beam.
    • Experience in creating and managing data orchestration workflows with Apache Airflow to efficiently schedule, monitor, and optimize data processing tasks.
    • Advanced knowledge of data structures and algorithms, networking, operating systems, particularly Unix/Linux, and version control systems.
    • Demonstrated expertise in both batch and real-time data stream processing, proficient in employing technologies such as Apache Kafka for designing and implementing solutions that address real-time data processing requirements.
    • Solid grasp of data warehouse design principles and hands-on experience in deploying data warehousing solutions on GCP/AWS, focusing on performance optimization and scalability.
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