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Mercury Insurance is seeking a Senior Data Engineer who will create production data pipelines and collaborate with analytics teams. This role requires strong skills in data engineering on Cloud platforms such as AWS and Snowflake, with the expectation of at least 6 years of relevant experience. A Bachelor's degree in a related field is essential, and candidates should possess strong problem-solving capabilities.
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Position Summary
As a Sr Data Engineer you will create production data pipelines for our advanced analytics and data science teams – as well as collaborate with other technical personnel on internal & external data sources and infrastructure needs. The Data Engineer will design, evaluate, and test data infrastructures and be a subject matter expert for all things data across the organization.
Position Summary
As a Sr Data Engineer you will create production data pipelines for our advanced analytics and data science teams – as well as collaborate with other technical personnel on internal & external data sources and infrastructure needs. The Data Engineer will design, evaluate, and test data infrastructures and be a subject matter expert for all things data across the organization.
Geo-Salary Information
State specific pay scales for this role are as follows:
$105,245 to $199,452 (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA)
$95,677 to $181,320 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)
$86,110 to $163,188 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV)
The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location.
Responsibilities
Essential Job Functions:
Design, build, and launch collections of high-quality big data/data lake solutions on Cloud platform preferably AWS, Snowflake that support multiple use cases across all departments, all products, and all states.
Solve our most challenging data integration problems, utilizing optimal ETL patterns, frameworks, query techniques, sourcing from structured and unstructured data sources.
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts.
The Data Engineer is an expert in all datalakes, data warehouses, and data cubes within Mercury, with no gaps in knowledge. Can efficiently and accurately extract and manipulate data from any source.
Collaborate with teams of data analysts and data scientists, who research and integrate algorithms to develop solutions to address complex data problems. Influence all functions across the organization to identify data opportunities to drive profitable growth. Proactively identify pain points that Analytics & Data Science face with our existing data models.
Leverages existing data infrastructure to fulfill all data-related requests, perform necessary data housekeeping, data cleansing, normalization, hashing, and implementation of required data model changes. Analyzes data to spot anomalies, trends and correlate similar data sets. Designs, develops and implements natural language processing software modules.
Other Functions May Be Assigned
Qualifications
Education
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