Key Responsibilities:

Design, build, and maintain data pipelines to support data processing, transformation, and analytics.
Monitor and troubleshoot data pipelines to identify and resolve issues in a timely manner.
Collaborate with cross-functional teams to understand data needs and develop solutions to address data challenges.
Develop and implement data quality checks to ensure the accuracy, completeness, and consistency of our data.
Optimize data processes and workflows to improve data access and reduce latency.
Create and maintain technical documentation, including data dictionaries, data flow diagrams, and standard operating procedures.
Conduct data analysis to identify trends, patterns, and insights to inform business decisions.
Stay up-to-date with emerging data technologies and industry trends to drive innovation and continuous improvement.

Qualifications:

Bachelor's degree in Computer Science, Information Systems, or related field.
Minimum of 3 years of experience in data engineering, data operations, or a similar role.
Proficient in SQL and experience working with relational databases.
Strong understanding of ETL processes and data warehousing concepts.
Experience with cloud-based data platforms, such as AWS, Azure, or Google Cloud.
Familiarity with data visualization tools, such as Tableau, Power BI, or Qlik.
Excellent problem-solving and analytical skills.
Strong communication skills and ability to collaborate with cross-functional teams.
Proven track record of delivering high-quality results in a fast-paced, dynamic environment.

Join our team as a Data Ops Engineer and be a part of our mission to turn data into actionable insights.

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