Position Title: Sr. Data Engineer
Employee Status: Full Time-Direct Hire with Client

Location: Remote

Purpose:

This crucial role will be responsible for designing, building, and maintaining scalable data pipelines and systems that power business insights, operational efficiency, and data-driven decision-making. The ideal candidate will have experience in data engineering, ideally within the insurance or financial services sectors, and will be passionate about leveraging data to drive innovation. You will work closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to support the development of data infrastructure and enhance analytics capabilities.

Responsibilities:

• Design, build, and maintain robust data pipelines and data storage solutions to support business analytics and reporting.

• Collaborate with data scientists and analysts to understand data requirements and ensure the availability of high-quality data for decision-making.

• Ensure data integrity, consistency, and accuracy across multiple systems and platforms.

• Optimize data flow and storage processes to improve performance and scalability.

• Implement data quality checks, monitoring, and troubleshooting to maintain seamless operations.

• Build and manage data models, integrating data from various sources into unified, accessible formats.

• Develop automated processes for data extraction, transformation, and loading (ETL).

• Collaborate with business units to define and deliver data solutions that meet business needs.

• Participate in code reviews and knowledge-sharing sessions to enhance the skills and capabilities of the technology team.

Work Requirements, Experience, Education, and Skills:

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.

• Minimum of 7 years of experience in data engineering, software development, or a related role, ideally in the insurance or financial services industries.

• Proficiency in SQL and experience with cloud platforms ( Azure).

• Strong understanding of ETL processes, data modeling, and database technologies (e.g., PostgreSQL, MySQL, NoSQL).

• Experience with data processing tools and frameworks such as Apache Spark, Hadoop, or similar technologies.

• Familiarity with data warehousing solutions and tools like Snowflake or Redshift.

• Ability to troubleshoot complex data issues and provide innovative solutions.

• Strong problem-solving, analytical, and communication skills.

• Ability to manage multiple priorities in a fast-paced environment.

Preferred qualifications:

• Experience working with insurance or financial services data and understanding the unique challenges in this industry.

• Familiarity with machine learning and AI technologies.

• Experience with data visualization tools such as Tableau, Power BI, or Looker.

• Certification in cloud platforms or big data technologies.