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Data Engineer

  • Full Time, onsite
  • McCarthy & Holthus
  • On Site Hybrid, United States of America
Salary undisclosed

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Job Description

Job Description

Working on groundbreaking projects here is a game-changer. I leverage advanced analytics and machine learning while collaborating with a brilliant team. The innovative environment has given me the tools and support to push the boundaries of data science and drive meaningful impact. - J. Gem, Data Scientist


As an AWS Data Engineer, you ll play a crucial role in shaping our data infrastructure and analytics capabilities. You'll design, build, and optimize scalable data pipelines and platforms, empowering our teams to harness data for strategic decision-making. This is an exciting opportunity to work with the latest AWS technologies and contribute to high-impact projects that drive our business forward.

Core Functions:

  • Data Pipeline Development: Design, deploy, and refine cutting-edge, scalable data pipelines on AWS to ingest, process, and store massive datasets for next-gen machine learning applications.
  • Machine Learning Integration: Collaborate with data scientists to deploy, manage, and enhance machine learning models on AWS, creating innovative models to improve performance and ensuring seamless integration with data pipelines.
  • User Interface Integration: Use your hands-on UX/UI development experience to work with front-end developers and UX/UI designers, integrating machine learning outputs into intuitive user interfaces for efficient data delivery.
  • AWS Infrastructure Management: Utilize AWS services such as S3, Redshift, Lambda, Glue, EMR, and QuickSight to build and maintain a robust data infrastructure, ensuring systems are secure, scalable, and high performing.
  • Automation and Optimization: Develop and implement automation scripts and tools, including Python, to streamline data workflows and model deployments. Continuously monitor and optimize performance, costs, and resource utilization, setting up alerts for any disruptions.
  • Collaboration and Communication: Work closely with data scientists, front-end developers, UX/UI designers, and product managers to deliver high-quality solutions that align with business goals.
  • Documentation: Maintain comprehensive and up-to-date documentation for data pipelines, infrastructure configurations, integration processes, and technology procedures.

Collaborative Responsibilities:

  • Data Source Identification: Identify and evaluate cutting-edge data sources to leverage the best information for transformative insights.
  • Data Analysis: Analyze data to uncover trends and patterns, validate results, and identify anomalies to ensure accuracy.
  • System Enhancement: Enhance and optimize databases and data systems, ensuring they run smoothly and adapt to evolving needs.
  • Performance Review: Review reports and performance indicators to identify issues, refine logic, and drive continuous improvement.

What We re Looking For:

  • Bachelor s degree in Computer Science, Engineering, Information Management, Data Science, or a related field.
  • 3+ years of experience in data engineering with a focus on AWS Cloud Services.
  • Strong proficiency in AWS services (S3, Lambda, Glue, EMR, QuickSight, etc.).
  • Experience with data pipeline tools and technologies (Apache Airflow, Spark, etc.).
  • Familiarity with Python, GitHub, SQL, and containerization (such as Docker), CI/CD pipelines, etc.
  • Strong analytical skills with attention to detail and accuracy in collecting, organizing, analyzing, and presenting data.
  • Exceptional communicator with the ability to thrive in a collaborative, team-oriented environment.
  • Outstanding critical thinking and problem-solving abilities, with a keen aptitude for analyzing and interpreting data.
  • Understanding of data models and process flows, with the capability to navigate and optimize them effectively.
  • Ability to work autonomously and contribute effectively within a team, with a strong capacity to adapt swiftly to evolving situations and ideas.

Work Schedule:

Work Monday to Friday from 8:00 a.m. to 5:00 p.m. Competitive wage range: $25 - $30 per hour, commensurate with experience and qualifications. This hybrid position requires onsite presence in our San Diego, California location 2-3 days per week after a 90-day training period and upon management approval.

Benefits:

Enjoy a balanced work/life environment with wellness programs, medical, dental, and vision coverage, 401(k) matching, and more. Full-time employees receive these benefits after a 30-day waiting period.

Physical Demands:

  • Frequently required to sit, talk, or hear.
  • Occasionally required to stand, walk, stoop, kneel, crouch, reach with hands and arms, and use hands to finger, handle, or feel.
  • Must occasionally lift and/or move up to 25 pounds.
  • Specific vision abilities required include close vision and the ability to adjust focus.

Work Environment:

Typical office environment with a quiet to moderate noise level.

Ready to take the next step? Apply now and be part of our thriving team!

https://mccarthyholthus.hrmdirect.com/employment/job-openings.php?search=true&&cust_sort1=200442

McCarthy & Holthus, LLP., and our affiliate companies, are Equal Opportunity Employers. We are committed to providing a work environment free from discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. We celebrate diversity and are dedicated to creating an inclusive environment for all employees.

As part of our commitment to maintaining a lawful and compliant workforce, McCarthy & Holthus, LLP., and our affiliate companies participate in the E-Verify program. All candidates who accept a job offer will be required to complete the E-Verify process to verify their employment eligibility in the United States.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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