Data Engineer II

Overview

Position Summary:

As a Data Engineer II you will create production data pipelines for our advanced analytics and data science teams — as well as collaborate with other technical personnel on internal and external data sources and infrastructure needs. The Data Engineer II will assist in 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: $89,906 to $170,421 (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA) $81,733 to $154,928 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME) $73,560 to $139,435 (UT, , 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.

• Design, build, and launch collections of high‑quality big data/data lake solutions on cloud platforms 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.

• Act as an expert in all data lakes, data warehouses, and data cubes; extract and manipulate data efficiently from any source.

• Collaborate with teams of data analysts and data scientists, integrating algorithms to develop solutions to 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.

• Leverage existing data infrastructure to fulfill all data‑related requests, performing necessary data housekeeping, cleansing, normalization, and hashing, and implementing required data model changes.

• Analyze data to spot anomalies, trends and correlate similar data sets.

• Design, develop, and implement natural language processing software modules.

• Other functions may be assigned.

• Bachelor’s degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, Information Systems, or related field.

• Actuarial experience/exams preferred.

• Or equivalent combination of education and/or experience.

3 or more years of experience in data analytics, data engineering, and/or data science.

3 or more years of experience in development of big data/data lake solutions on cloud platforms, preferably AWS (S3, Glue/EMR, Athena, App Flow) or Snowflake.

3 or more years of experience in Python, Java and/or Scala programming.

3 or more years of experience in writing SQL statements and query performance tuning.

3 or more years of experience in RDMS or MPP databases, preferably AWS Redshift or Snowflake.

• 3 or more years of experience working with MDM (Master Data Management), preferably Reltio.
• 1 or more years of experience working with AI technologies in a production environment.

• A high‑level specialist who regularly interacts and works with senior management.
• Expert at analyzing data to identify gaps and inconsistencies.
• Able to multitask, prioritize, and manage time effectively.
• The ability to think conceptually, analytically and creatively, comfortable with ambiguity.
• Experience managing and communicating data plans and data models to internal clients.
• Demonstrated solid understanding, and passion for all areas of data/analytics engineering best practices.
• Demonstrated expert skills in data mining and data analytics.
• Expert in Python and/or SQL programming; some experience with R preferred.
• Solid experience with cloud‑based advanced data and analytics environment.
• Knowledge of working with AWS, Git Hub, and other cloud‑based infrastructure.
• Expert data skills and the ability to work with large structured and unstructured data sources.
• Excellent problem‑solving skills required.
• Excellent analytical and critical thinking required.
• Excel…