Data Engineering Manager

About the position

As a Data Engineering Manager at Amica, you will be responsible for building high quality, scalable, and resilient distributed systems that propel analytics platforms. This includes managing and optimizing data pipelines that deliver curated data for key analytics consumers and initiatives. You will work on a variety of near real-time and batch analytical processes that enable business users to make critical decisions. The role requires a strong combination of IT, data governance, analytics, and creative skills, and plays a pivotal role in extending the next generation of the data ecosystem and operationalizing urgent data and analytics initiatives.

Responsibilities

• Manage 3-5 employees
• Responsible for maintenance and development of Life Cloud Data Warehouse (Snowflake)
• Work with business units to develop data assets
• Work with Reporting and Analytics group to support data needs
• Responsible for timeliness, accuracy, and completeness of data
• Manage all data operations/workflows from sources to the warehouse (AWS)

Requirements

• Bachelor's degree in data management, computer science, information systems, mathematics, data/analytics or a related field or equivalent work experience is required.
• Work experience in data management disciplines including data integration, data modeling, optimization and data quality that is commensurate with job level
• Basic experience working with data discovery, analytics, visualization and business intelligence tools.
• Strong experience with scripting languages such as Python, PowerShell, or Linux
• Strong experience with managing and maintaining Snowflake Cloud environments
• Intermediate understanding of data science platforms R and Python.
• Strong understanding of ETL/ELT platforms
• Thorough knowledge of relational and non-relational database theory and structured query language (SQL).
• Superior ability to design, build and implement data pipelines, ETL processes, and data structures.
• Demonstrated success integrating large, heterogeneous datasets and automating repetitive data preparation tasks.
• Skilled working across multiple deployment environments including cloud, on-premises and hybrid.
• Adept applying software engineering methodologies and DevOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows across the organization.
• Strong management skills, which include mentoring, coaching, and developing less experienced staff.
• Persuasive, with excellent interpersonal skills and able to interact effectively with others, including team members and senior management.

Benefits

• Medical, dental, vision coverage, short- and long-term disability, and life insurance
• Paid Vacation - at least 13 vacation days in the first 12 months
• 14 paid holidays observed
• 6 days sick time at hire, 6 additional days sick time at 90 days of employment
• Generous 401k with company match and immediate vesting
• Annual Success Sharing Plan
• Generous leave programs, including paid parental bonding leave
• Student Loan Repayment and Tuition Reimbursement program
• Generous fitness and wellness reimbursement
• Employee community involvement
• Opportunities for advancement in a successful and growing company