Data Engineer

Ringside Talent • Full-time • Cleveland, OH, US • $110k - $130k / year • 5d ago

Our Cleveland Client is actively seeking a Data Engineer to join their team. The ideal candidate aligns with the responsibilities and qualifications outlined below.

Responsibilities:

Design, build, and maintain scalable and efficient data pipelines to extract, transform, and load (ETL) data from various sources into our data infrastructure.
Develop and optimize data warehouse and data lake architectures to ensure efficient storage, retrieval, and analysis of large datasets.
Collaborate with data analysts, data scientists, and other stakeholders to understand data requirements and implement data integration solutions.
Develop and implement data quality processes and measures to ensure the accuracy, completeness, and consistency of data within our systems.
Identify and resolve performance issues within the data infrastructure, optimize data processing and query performance, and implement data caching strategies where applicable.
Ensure data security and compliance with regulatory requirements by implementing appropriate access controls, data encryption, and data anonymization techniques.
Establish and enforce data governance policies, standards, and best practices to maintain data integrity, privacy, and security.
Investigate and resolve data-related issues, provide technical support to users, and perform root cause analysis to prevent future occurrences.

Qualifications:

3+ years of experience as a Data Engineer or in a similar role, with a strong background in data management, ETL processes, and database technologies.
Proficiency in programming languages such as Python, Java, or Scala for data processing and manipulation.
Experience with data integration tools, such as Apache Kafka, Apache Nifi, or Informatica.
Strong understanding of data modeling, database design principles, and SQL.
Knowledge of data warehouse architectures (e.g., Kimball, Inmon) and experience with data warehousing technologies like Snowflake, Redshift, or BigQuery.
Familiarity with distributed computing frameworks (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP).
Experience with version control systems (e.g., Git) and agile software development methodologies.
Solid understanding of data security and privacy principles and experience implementing data governance practices.