Investment Data Engineer

TriCom Technical Services

Kansas City, MO, United States

2 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

FactSet Agile Methodology Amazon Web Services Databases Continuous Integration Data Architecture Data Governance Extract Transform Load (ETL) Data Structures Relational Databases Document-Oriented Databases Amazon DynamoDB

+25 more

Xbrl JSON Python (Programming Language) PostgreSQL MongoDB NoSQL Oracle (Applications) Reference Data Power BI Simple Data Format PL-SQL SQL Databases Data Streaming Tableau (Software) Extensible Markup Language (XML) Enterprise Data Management Parquet Snowflake Gitlab Git Data Layers Information Technology Data Analytics Data Management Data Pipelines

Job description

Our client is seeking an Investment Data Engineer to support investment data needs within their enterprise Data Platform and related transactional databases. This role will design, document, and implement data architectures, data models, and data pipelines and will be heavily involved in a full modernization of how the valuations organization receives, stores, and works with market and securities data. This Investment Data Engineer will partner daily with the Platform Team in an Agile environment and work closely with business stakeholders to reimagine legacy data flows rather than simply maintain them., * Analyze complex investment and related data sources to design and document data architectures, data models, and data pipelines.

Create and maintain the data structures housing data across the various platform data layers.
Build and maintain data pipelines that populate those layers including update tasks.
Develop and maintain pipeline monitoring, data quality, and data governance processes.
Partner with data architects, data engineers, data stewards, business owners, and project managers on a major modernization of the investment data stack.

Requirements

Bachelor’’s degree in Computer Science, Data Analytics, Data Science, Mathematics/Statistics, or a related analytical field.
Experience with SQL, PL/SQL, and RDBMS (Oracle, PostgreSQL).
Experience with Snowflake and AWS.
Experience with Python and ETL/ELT development.
Experience with Git/GitLab and CI/CD practices.

Preferred

Experience with investment and market data including securities, stocks, bonds, and credit rating provider data.
Familiarity with financial reference data including CUSIP, ISIN, and SEDOL.
Experience consuming financial data vendor feeds including S&P Global, Bloomberg, or FactSet.
Experience with NoSQL (MongoDB/DynamoDB) and file formats including JSON, Parquet, XML, and XBRL.
Exposure to Tableau, Power BI, or ThoughtSpot; Agile methodology.