Opportunity:
Olmstead drives business success by helping clients build and leverage a strong data foundation. The right data strategy can reduce risk, increase productivity, improve decision making, and fuel innovation.
We are seeking a hands-on detail-oriented data engineer with investment management industry experience. Candidates will have experience with writing Extract Transform Load (ETL) processes, SQL, DevOps/DataOps, job orchestration, data modeling, data profiling, database design, and data governance. They are not afraid to roll up their sleeves, challenge the status quo, leverage best practices, and grow beyond their comfort zone. They are an excellent communicator that uses precise language and frames messaging in business terms.
As a valued member of our expert data management consulting team, you will engage clients to document and analyze their data landscape. Analysis will help the client grow, develop new capabilities, and optimize data management. You will deliver a wide range of data engineering solutions, such as data integrations, data migrations, data warehousing, query optimizations, and advanced analytics.
Responsibilities:
- Aid current state assessments by collecting information on data sources, data flows, data transformations, and data delivery timelines
- Proactively analyze data flows to answer key questions from stakeholders or out of self-initiated curiosity with an eye for what drives business performance, investigating and communicating areas for improvement in efficiency and productivity
- Collaborate with team members and client stakeholders to understand data engineering needs and deliver solutions
- Produce project deliverables that may include ETL processes, stored procedures, data integration solutions, documentation, and job orchestration
- Trace data requirements, data sources, and data flows for data engineering processes
- Apply best practices
Qualifications:
- Possess strong business knowledge of the investment management industry and common data management operations
- Data modeling expertise for investment data domains, such as security master, accounts, holdings, transactions, etc.
- Experience creating ETL solutions using a leading ETL tool or data management platform
- Strong hands-on SQL and programming skills with the ability to learn other tools
- Expertise with relational databases, Snowflake, data lakes, JSON, XML, document stores, and REST web services
- Familiarity with data management best practices and patterns
- Experience with building cloud solutions, preferably on Azure
- DevOps and agile delivery experience, preferably DataOps
- Experience with DBT, Power BI, PowerShell, and Python is desired
- Experience with Bloomberg, FactSet, Salesforce, Seismic, and Vermillion is desired
- Bachelor’s degree required