Data Engineer

Covista

$74K — $133K *
Lisle, IL 60532In-Person
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's Degree in Computer Science, Computer Engineering, Software Engineering, or related field required.
  • Preferred Master's Degree in relevant technical field.
  • Over three years of experience in building data lakes and cloud data platforms.
  • Proficiency in GCP technologies: BigQuery, Composer, GCS, DataStream, and Dataflows.
  • Expertise in SQL and Python programming.
  • Hands-on experience with Airflow for workflow management and building operators.
  • Ability to optimize queries for performance and scalability.

Responsibilities

  • Collaborate with business, IT, analysts, and data science teams to gather requirements.
  • Develop and support high-performance data pipelines for data flow.
  • Optimize performance, scalability, and reliability of data pipelines.
  • Ensure quality of critical data and implement remediation plans for data issues.
  • Document designs and support strategies for data pipelines.
  • Capture and socialize data lineage and operational metadata.
  • Troubleshoot and resolve data engineering challenges as they occur.

Benefits

  • Health, dental, vision, life, and disability insurance.
  • 401k Retirement Program with 6% employer match.
  • Flexible Time Off (FTO) Policy.
  • 12 Paid Holidays.
  • Eligibility for an annual incentive program based on performance.
Full Job Description
Job Description
  • Work closely with various business, IT, Analyst and Data Science groups to collect business requirements.
  • Develop, deploy and support high performance data pipelines both inbound and outbound.
  • Optimize data pipelines for performance, scalability, and reliability.
  • Ensure quality of critical data element, prepare data quality remediation plans and collaborate with business and system owners to fix the quality issues at its root.
  • Document the design and support strategy of the data pipelines.
  • Capture, store and socialize data lineage and operational metadata.
  • Troubleshoot and resolve data engineering issues as they arise.

Qualifications
  • Bachelor's Degree Computer Science, Computer Engineering, Software Engineering, or other related technical field Required.
  • Master's Degree Computer Science, Computer Engineering, Software Engineering, or other related technical field Preferred.
  • Three (3) plus years of experience in building data lakes and cloud data platforms.
  • Experience working with GCP technologies like BigQuery, Composer, GCS, DataStream, Dataflows.
  • Expert knowledge on SQL and Python programming.
  • Experience working with Airflow as workflow management tools and build operators to connect, extract and ingest data as needed.
  • Experience in tuning queries for performance and scalability
  • Experience working in agile environment.
  • Excellent problem-solving and critical thinking skills.

Additional Information

In support of the pay transparency laws enacted across the country, the expected salary range for this position is between $74,064.94 and $133,901.96. Actual pay will be adjusted based on job-related factors permitted by law, such as experience and training; geographic location; licensure and certifications; market factors; departmental budgets; and responsibility. Our Talent Acquisition Team will be happy to answer any questions you may have, and we look forward to learning more about your salary requirements. The position qualifies for the below benefits.

Covista offers a robust suite of benefits including:
  • Health, dental, vision, life and disability insurance
  • 401k Retirement Program + 6% employer match
  • Participation in Covista's Flexible Time Off (FTO) Policy
  • 12 Paid Holidays
    For more information related to our benefits please visit:
    https://careers.covista.com/benefits
    You are also eligible to participate in an annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

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