Investment Data Architect/Technical Architect

SABIO Infotech; Pittsburgh (Allegheny County); Hybrid; USD 120,000 - 190,000; Full time

Job summary

SABIO Infotech in Pittsburgh (hybrid) is seeking a Technical Architect/Investment Data Architect to lead data architecture and strategy for investment data.

You will analyze data, design models, and govern data as a product across domains, collaborating with PMs, risk, research, and engineering.

Qualifications

• 7–12 years in investment management or financial services data.
• Deep SQL skills and query tuning.
• Oracle database experience (PL/SQL a plus).
• Experience with Hadoop/PySpark for distributed processing.
• Familiarity with GraphQL and API-based data delivery.

Responsibilities

• Analyze investment data directly using SQL against Oracle.
• Design target-state data models and data-serving patterns.
• Translate ambiguous needs into clear problems and backlogs.
• Lead design reviews with engineers and platform teams.
• Own data domains: security master, market data, holdings, risk, ESG data.
• Govern data as a product with quality SLAs and lineage.
• Evaluate market data vendors and platform options.

Skills

Investment data domain knowledge

Hybrid stakeholder collaboration

Tools

SQL

Oracle

Hadoop

PySpark

GraphQL

Job description

Role- Technical Architect/Investment Data Architect

Location : Pittsburgh PA (Hybrid - 2 OR 3 Days)

Need Someone with Asset Management Background

What You'll Do

• Analyze the data yourself --- profile, query, and reconcile investment data directly (SQL against Oracle, distributed processing on Hadoop/PySpark) to answer business questions and pressure-test assumptions before they become designs.
• Design the architecture --- target-state data models, integration patterns, and data-serving designs (including GraphQL and other API layers) that balance performance, cost, and maintainability.
• Drive the business discussion --- turn ambiguous needs from PMs, research, risk, and client reporting into a clear problem statement, prioritized backlog, and outcomes stakeholders care about.
• Drive the technical discussion --- lead design reviews with engineering and platform teams; make and defend trade-offs on modeling, storage, processing, and distribution.
• Own the data domains --- security master and reference data, market/pricing data, holdings and transactions, benchmarks, performance and attribution, risk, and ESG/alternative data.
• Govern data as a product --- ownership, quality SLAs, lineage, and shared definitions so a "position" or an "AUM" number means the same thing everywhere.
• Rationalize vendors and platforms --- evaluate market data and platform vendors (Bloomberg, LSEG/Refinitiv, FactSet, MSCI, ICE, Aladdin/other OMS) against coverage, cost, and redundancy.

Required Skills & Experience

• 7--12 years across investment management, financial services data, or related consulting, with real exposure to the buy-side investment lifecycle.
• SQL --- advanced query writing and performance tuning.
• Oracle --- deep experience against Oracle databases (PL/SQL a plus).
• Hadoop --- working knowledge of the big-data ecosystem (HDFS, Hive, etc.).
• PySpark --- building and optimizing distributed data processing.
• GraphQL --- designing and exposing data through GraphQL / API-based serving layers.
• Working fluency in investment data domains (security master, benchmark files, performance return streams, and how they connect).
• Proven ability as a genuine hybrid --- trusted by business stakeholders and respected by engineers.
• Data modeling and architecture experience --- able to design a target state, not just critique one.