[Hiring] Data Engineer / Data Architect Consultant @IANS

Role Description

IANS is looking for a Data Engineer / Data Architect Consultant to build the foundational data architecture that powers all of our products as we become a data-first company. You'll design and implement scalable data systems across Azure SQL Server, PostgreSQL, Elasticsearch, Salesforce integrations, and Azure cloud services — creating the infrastructure that enables initiatives like content metadata enrichment, new data-driven product offerings (e.g., Vendor Intelligence), analytics, and AI/ML workloads.

This is about building the foundation once and building it right, so it scales across everything we do. This is a full-time, ongoing consulting engagement — we hire contractors to keep them as long as we can.

What You'll Do

• Design and build a scalable, org-wide data architecture that serves as the backbone for all current and future products.
• Design, build, and maintain data pipelines and ETL/ELT processes across Azure SQL Server, PostgreSQL, Elasticsearch, and third-party sources (Salesforce, APIs).
• Evaluate and support a potential migration from MSSQL to PostgreSQL, including feasibility analysis, schema translation, deadlock remediation, performance benchmarking, and migration planning.
• Build and maintain a centralized data warehouse or data platform to support analytics, reporting, AI/ML workflows, and our broader data-as-a-service.
• Architect metadata models, taxonomies, and tagging systems that enable content enrichment across products (e.g., tagging content with vendors, team size, revenue, industry).
• Collaborate with engineering, product, and AI teams to define data models and ensure clean, consistent data flows across systems.
• Implement data quality checks, monitoring, and alerting to maintain data integrity across all data products.
• Document data architecture, lineage, and dictionary standards for the engineering team.
• Support and improve existing Azure SQL databases, Redis caching layers, and Elasticsearch clusters.
• Identify and resolve data bottlenecks, query performance issues, and infrastructure gaps.

Success in This Role

• 30 days: Understand the current data landscape — databases, pipelines, integrations, and pain points. Deliver a data architecture assessment with prioritized recommendations.
• 60 days: Key pipelines improved or rebuilt. Foundational data platform architecture designed and in progress. PostgreSQL evaluation underway with initial benchmarking against MSSQL. Data warehouse foundations in place.
• 90 days: Reliable, documented data infrastructure supporting product, analytics, and AI workloads. Metadata and enrichment patterns established for product teams to build on. Monitoring and data quality processes running. Clear roadmap for data-as-a-service expansion.

Qualifications

• 4–7 years of experience in data engineering, data architecture, or a related role.
• Advanced or fluent spoken English.
• Strong expertise in Microsoft SQL Server — schema design, stored procedures, views, performance tuning, and query optimization.
• Experience with PostgreSQL — schema design, migrations, performance tuning, and tooling (or demonstrated ability to evaluate and adopt it).
• Hands-on experience building and managing ETL/ELT pipelines (FiveTran, SSIS, Python, or similar).
• Solid experience with Azure cloud services — Azure SQL, Azure Functions, Azure Redis Cache, and related data tooling.
• Experience designing metadata models, taxonomies, or tagging systems for content enrichment or data products.
• Working knowledge of Elasticsearch for search indexing and data retrieval.
• Experience designing and maintaining data warehouses or analytical data stores.
• Familiarity with data integration from Salesforce or other CRM/SaaS platforms via APIs or connectors.
• Strong documentation, communication, and problem-solving skills.
• Experience designing and implementing database sharding and partitioning strategies to support high-throughput, horizontally scalable applications.
• Self-motivation and ability to work effectively in a small, collaborative remote team.

Nice to Have

• Experience with Python for data processing and automation.
• Familiarity with js/Express backend services and how they interact with data layers.
• Experience supporting AI/ML data pipelines (training data preparation, vector databases, embeddings).
• Knowledge of MongoDB, n8n, or other NoSQL databases.
• Exposure to GitHub Actions CI/CD workflows.
• Experience with data governance, cataloging, or compliance frameworks.
• Background in BI/reporting tools (Power BI, Looker, Tableau or similar).

Details

• Location: Remote — Bogotá, Colombia
• Hours: Up to 40/week
• Duration: 12 months to start with likely extension based on impact
• Type: Consulting engagement