Data Engineer at Boston Mutual Life Insurance Company

Omaha, Nebraska, United States -

Full Time

Start Date

Immediate

Expiry Date

11 Feb, 26

Salary

0.0

Posted On

13 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Azure Databricks, Azure Synapse Analytics, Azure Data Factory, SQL, Python, Spark, Data Governance, Data Quality Management, ETL, Business Intelligence, Agile Development, Data Analysis, Data Warehousing, Visualization Tools, Technical Documentation

Industry

Description

All Boston Mutual employees who interact with our policyholders, our producers, and our BML associates embrace the principles of our brand and service philosophy. We are all brand ambassadors. Both our words and our behaviors matter. We share a common service philosophy and pride ourselves in living the BML brand promises every day, one interaction at a time. The following statements represent what Boston Mutual stands “FOR” – it is what makes us different and better in the market we serve. * We are FOR being a progressive life insurance company offering financial peace of mind to working Americans and their families. * We are FOR providing practical and affordable products designed for those we serve. * We are FOR making it easy to secure a level of financial protection with a portfolio of products – beginning with life insurance. * We are FOR providing a personalized customer experience to our policyholders and producers. * We are FOR acting in the best interests of our policyholders, producers, employees and the communities in which we live and serve – representing the goodness of mutuality in all we do. We do our best to: * Demonstrate a desire to assist * Listen for understanding and respond empathetically * Explain things in a manner that is easy to understand * Be knowledgeable students of our business * Take full ownership to resolve questions and issues * Be professional, polite and courteous * Leave our customers and associates “better than where we found them” The Data Engineer reports directly to the Director - Data and Analytics The primary responsibilities of a Data Engineer are to focus on building our data lake using Databricks, Synapse Analytics and Azure Data Factory in the Azure ecosystem. In this role you will work with a team of developers, data product owners, scrum masters, business analysts and business customers in an agile environment. You will participate in the entire software development lifecycle, including: working with various departments on requirements gathering, translating business requirements into detailed system and technical requirements, functional and technical design, development, testing, deployment, and support. You will contribute to all data management aspects, including data governance, data quality management, master data management, enterprise data integration by analyzing raw data, writing data pipelines in Azure Data Factory, SQL, Python, and Spark, and solving data issues as they arise during development and after deployment.. The Data Engineer is expected to: * Design, develop and implement scalable batch/real-time data pipelines to integrate data from a variety of sources into an Azure data warehouse and data lake * Partner with analytics and actuarial team to understand the current use cases and supply clean and consistent data models * Build consistent data models that act as the source of truth for all metrics within the company * Identify data needs & build comprehensive business intelligence solutions to help the team make faster & better decisions, backed by data * Handle ad hoc data and analytics requests, while addressing long-term stakeholder needs and driving insights for the executive leadership team * Proactively manage stakeholder expectations, monitor and manage data integrity, and resolve data issues * Create and maintain technical documentation. * Guide and deliver meaningful and thorough code reviews. * Design, code, test, document, and troubleshoot deliverables * Maintain awareness of and ensure adherence to the standards regarding security and privacy. * Ability to perform Data Analysis and Data Quality tests and create audits for the ETLs. * Perform Continuous Integration and deployment using Azure DevOps and git * Must be a very good communicator and should be analytically sound * Create and maintain optimal data pipeline/flow architecture. * Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Qualifications Education: * Bachelor’s degree or equivalent work experience required. Experience: * 3+ Years similar work experience Knowledge Requirements: 1. Experience/familiarity with tools like Azure Databricks, Azure Synapse Analytics and Azure Data Factory, Delta Lake, Parquet, and Spark SQL 2. Experience with Data Lakes, Data Warehouse Concepts, and Dimensional Data Models. 3. Experience with Tableau, Power BI, Qlik or similar as visualization tool development 4. Experience building and maintaining production data pipelines,,ETL, or databases 5. Good written and verbal communication skills 6. Experience in SQL – Python, Powershell and Spark helpful but not necessary 7. Experience working with Microsoft BI stack (SSIS/SSRS/SSAS) and Microsoft SQL Server. 8. Experience with agile development methods Hybrid Work Model At our Canton location, employees will be on site Monday - Thursday. At our Omaha location, employees will be on site 2 days per week. Boston Mutual is an equal opportunity employer, and does not discriminate on the basis of race, color, age, religious creed, national origin, ancestry, sex, sexual orientation, gender identity, genetic information, disability, military service, veteran status, family status, pregnancy, or any other characteristic protected by federal or state laws. Boston Mutual is a drug-free workplace. #LI-Hybrid

Responsibilities

The Data Engineer will focus on building the data lake using Databricks, Synapse Analytics, and Azure Data Factory. Responsibilities include designing and implementing scalable data pipelines and collaborating with various teams to ensure data integrity and quality.