Big Data Engineer

Big Data Engineer (Fintech / Investment advisor intelligence Platform)

Company: RIA Growth Catalyst (dba RIA Catalyst)

Location: Remote (Europe and India timezones preferred)

Type: Contract or Full-Time (flexible)

About RIA Growth Catalyst

RIA Growth Catalyst is a data-first fintech platform powering inorganic and organic growth across the Registered Investment Advisor (RIA) ecosystem. We aggregate, normalize, and enrich large-scale regulatory, firm, advisor, and transaction data—transforming it into predictive insights that support M\&A, advisor recruiting, and strategic decision-making.

Our product lives and dies by data accuracy, pipeline reliability, and scalable architecture. We’re building what many in the industry call an “IAPD 2.0”—and we’re looking for a Big Data Engineer who wants to own the foundation of that system.

Role Overview

We’re seeking a Big Data Engineer to design, build, and maintain the data pipelines that power our analytics platform and AI-driven insights. You’ll work closely with product, analytics, and leadership to ensure that raw regulatory and third-party data becomes clean, queryable, and production-ready—at scale.

This is a hands-on engineering role, not a dashboard-only or research role. You’ll be responsible for ingestion, orchestration, transformation, and performance optimization across our cloud-native data stack.

Key ResponsibilitiesData Architecture \& Pipelines

Design and maintain scalable data pipelines for ingesting large, frequently updated datasets (e.g., SEC filings, firm metadata, historical records).

Build and orchestrate workflows using Python + Airflow to ensure reliable, automated data processing.

Manage incremental updates, backfills, schema evolution, and historical versioning with precision.

Data Warehousing \& Storage

Optimize analytical data models in BigQuery for fast, cost-efficient querying.

Design and maintain relational schemas in Postgres / AlloyDB to support application-layer use cases.

Manage data storage and lifecycle policies in Google Cloud Storage (GCS).

Data Quality \& Reliability

Implement validation, reconciliation, and monitoring to ensure data accuracy, completeness, and consistency.

Identify and resolve pipeline failures, performance bottlenecks, and data anomalies proactively.

Build logging and observability into workflows so issues are caught before they impact users.

Collaboration \& Product Enablement

Partner with product, analytics, and leadership to translate business questions into technical data solutions.

Support downstream use cases including dashboards, scoring models, exports, and APIs.

Prepare datasets that are ML-ready, even if you’re not training models directly.

Tech Stack (What You’ll Actually Use)

Python

Apache Airflow

SQL (BigQuery)

Google Cloud Storage (GCS)

Postgres / AlloyDB

Git-based workflows \& cloud-native infrastructure

QualificationsRequired

Strong experience building production-grade data pipelines using Python and SQL.

Hands-on experience with Airflow for orchestration and workflow management.

Deep understanding of analytical data modeling and query optimization in BigQuery or similar warehouses.

Experience working with cloud-native data stacks (GCP preferred).

Strong command of relational databases (Postgres or equivalent).

Ability to reason about data quality, lineage, and performance—not just ingestion.

Nice to Have

Experience working with regulatory, financial, or time-series datasets.

Familiarity with data products that serve external users (SaaS, fintech, analytics platforms).

Exposure to ML feature pipelines or predictive modeling workflows.

Comfort working in a fast-moving startup environment with evolving requirements.

Why This Role Matters

At RIA Growth Catalyst, data isn’t support—it is the product. The pipelines you build directly impact acquisition scores, market insights, and strategic decisions made by PE firms, aggregators, and RIAs across the country.

If you enjoy owning systems end-to-end, working close to the business, and turning messy real-world data into durable infrastructure, you’ll thrive here.

Job Types: Part-time, Contract

Pay: $15.00 - $35.00 per hour

Expected hours: 10 – 25 per week

Work Location: Remote