Full Stack Data Engineer

Company Overview: Business Integration Partners (BIP) is Europe’s fastest growing digital consulting company and are on track to reach the Top 20 by 2030, with an expanding global footprint in the US (New York, Charlotte, Chicago, and Houston). Operating at the intersection of business and technology, we design, develop, and deliver sustainable solutions at pace and scale, creating greater value for our customers, employees, shareholders, and society. BIP specializes in high-impact consulting services across multiple industries with 6,000 employees worldwide. Our Financial Services business serves Capital Markets, Insurance and Payments verticals, supplemented with Data & AI, Cybersecurity, Risk & Compliance, Change Management and Digital Transformation practices. We integrate deep industry expertise with business, technology, and quantitative disciplines to deliver high-impact results for our clients. BIP is currently expanding its footprint in the United States, focusing on growing its Capital Markets and Financial Services lines. Our teams operate at the intersection of business strategy, technology, and data to help our clients drive smarter decisions, reduce risks, and stay ahead in a fast-evolving market environment. About the Role: We are seeking a hands-on Full Stack Data Engineer to design, build, and enhance data products supporting front-office investment workflows across Portfolio Management, Trading, Risk Analytics, and related business functions. This role sits at the intersection of data engineering, software engineering, front-end development, and investment data. The successful candidate will work across the full data lifecycle—from source ingestion and transformation through database design, curated datasets, APIs, and modern React-based user experiences. The ideal candidate brings strong Python, SQL, React, and API development experience combined with an understanding of investment-management data, including positions, transactions, pricing, market data, security master, reference data, accounts, portfolios, and risk/analytics data. This is a hands-on engineering position within a globally distributed team and is well suited to an engineer who can take meaningful ownership of production data products while partnering closely with front-office and technology stakeholders. Key Responsibilities: Design, build, and enhance scalable data ingestion and transformation pipelines supporting critical front-office and investment data sources, including near-real-time data where required.Develop database structures and data models spanning source-aligned data through curated, consumption-ready datasets.Work with investment data including positions and holdings, transactions, security and instrument master data, pricing and valuations, market data, reference data, accounts, portfolios, investment structures, and risk and analytics data.Develop REST and/or GraphQL APIs and data-access services that enable applications and analytics workflows to efficiently consume curated investment datasets.Build intuitive React-based user interfaces that enable Portfolio Managers, Traders, Risk professionals, and other users to explore, validate, and interact with data.Partner with Portfolio Management, Trading, Risk, Data Engineering, and other stakeholders to understand business workflows and translate requirements into scalable technical solutions.Investigate and improve existing datasets and pipelines with a focus on data quality, reconciliation, reliability, query performance, lineage, transparency, and usability.Trace and troubleshoot data issues end-to-end across source systems, transformations, databases, APIs, and user-facing applications.Apply strong software engineering practices including automated testing, code reviews, documentation, version control, and production validation.Leverage modern AI-assisted development tools to accelerate engineering, testing, debugging, documentation, and data analysis.Explore opportunities to make trusted enterprise investment data accessible to AI assistants, agents, and other AI-enabled workflows.Participate in production support and take ownership of resolving data and application issues. Required Skills and Experience: 6–8+ years of professional software engineering experience, with meaningful hands-on experience across data/backend engineering and front-end development.Strong programming skills in Python, including experience building production-quality data pipelines, services, or applications.Strong experience developing modern web applications using React and JavaScript/TypeScript.Advanced SQL skills with practical experience designing, querying, and optimizing relational or analytical database structures.Strong experience building data pipelines involving ingestion, transformation, validation, and delivery of large or complex datasets.Experience developing and/or consuming REST and GraphQL APIs.Experience working with cloud-based data environments and modern data warehouses; Azure and Snowflake are strongly preferred.Strong understanding of the full data lifecycle from source ingestion and transformation through databases, curated datasets, APIs, applications, and analytics consumption.Experience troubleshooting complex data issues across multiple technology layers.Experience working within asset management, investment management, capital markets, or a similarly data-intensive financial services environment.Strong understanding of front-office investment data concepts including positions/holdings, transactions, pricing, market data, security master, reference data, account and portfolio data, and risk/analytics data.Understanding of how investment data is consumed by Portfolio Managers, Traders, Risk professionals, and investment analytics teams.Hands-on experience with modern AI-assisted software development tools such as Codex, Claude, Cursor, GitHub Copilot, or similar technologies.Strong delivery ownership with the ability to operate effectively in a fast-paced, globally distributed engineering environment.Excellent communication skills and ability to collaborate effectively with both technical teams and front-office business stakeholders. Preferred Qualifications: Direct experience supporting Portfolio Management, Trading, Risk, or other front-office investment workflows.Experience working with private markets, alternative investments, or Private Equity data.Experience with Snowflake data modeling and performance optimization.Experience building or supporting near-real-time or event-driven financial data pipelines.Familiarity with Spark or other distributed data-processing frameworks.Experience developing semantic or analytics-ready datasets for platforms such as Tableau, Power BI, Sigma, or Pyramid.Exposure to AI/LLM application development, including retrieval, tool use, agents, structured outputs, or natural-language interfaces over enterprise data.Java development experience in addition to Python.Experience building data products designed for both human users and AI-enabled applications. Compensation: **The base salary range for this role is $130,000 - $175,000** Benefits: Choice of medical, dental, vision insurance.Voluntary benefits.Short- and long-term disability.HSA and FSAs.Matching 401k.Discretionary performance bonus.Employee referral bonus.Employee assistance program.11 public holidays.20 days PTO.7 Sick Days.PTO buy and sell program.Volunteer days.Paid parental leave.Remote/hybrid work environment support. For more information about BIP US, visit https://www.bip-group.com/en-us/. Equal Employment Opportunity: It is BIP US Consulting policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship, or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds. BIP US provides a reasonable range of compensation for our roles. Actual compensation is influenced by a wide array of factors including but not limited to skill set, education, level of experience, and knowledge.