About the role
We are looking for a Senior Data Engineer to architect and build an enterprise data platform from the ground up on Snowflake and Azure, owning the full stack from infrastructure provisioning through pipeline development, data modeling, governance, and observability. You will build Bronze/Silver/Gold data models using SQLMesh, provision all platform resources with Terraform, implement CI/CD pipelines via GitHub Actions, and enforce HIPAA-aligned data handling and Snowflake RBAC standards. The role is a solo senior contributor position requiring high ownership and the ability to deliver production-grade platform without specialist support teams.
What you will do
- Develop and maintain scalable data pipelines ingesting from enterprise source systems (EHR, ERP, CRM, SaaS, PMS) into Snowflake using Azure Data Factory, Azure Event Hub, and ADLS Gen2.
- Build and optimize analytics-ready data models (Bronze/Silver/Gold layers) using SQLMesh.
- Provision and manage all platform infrastructure through Terraform, including Snowflake objects, Azure resources, networking components, and access controls, following infrastructure-as-code standards.
- Implement CI/CD pipelines using GitHub Actions for automated testing, environment promotion, and controlled multi-environment releases (dev/test/staging/production).
- Design and enforce data governance, security, and access control standards, including Snowflake RBAC, row-level security, column masking, and HIPAA-aligned data handling practices.
- Configure and maintain cloud networking and private connectivity, including Azure Private Endpoints, Private Link, Private DNS zones, managed identities, and network security groups.
- Build and operate platform-wide observability using Datadog or equivalent, covering pipeline health, data freshness, anomaly detection, alerting, and end-to-end data lineage.
- Write production-grade Python for ingestion utilities, data quality frameworks, and platform integrations, including reconciliation checks and automated tests that block bad data from reaching production.
- Apply Agile delivery practices including sprint planning, standups, and backlog refinement in collaboration with analytics and business stakeholders.
- Establish and document data engineering standards, reusable patterns, and best practices that scale with the platform and organization.
- Diagnose and resolve production issues across pipelines, infrastructure, networking, security, and platform services.
Must haves
- 4+ years of hands-on data engineering experience with full production pipeline ownership in a lean, high-ownership environment (you build it, you own it, you support it).
- Proven track record building and managing cloud data platforms, featuring deep expertise in Snowflake administration and performance tuning.
- Strong SQL and data modeling fundamentals, including Kimball methodology, dimensional design, and Slowly Changing Dimension (SCD) management.
- Production experience with SQLMesh or DBT operating in a warehouse-centric architecture.
- Hands-on experience ingesting data from REST APIs and SQL Server using Azure Data Factory (ADF) and Azure Functions.
- Hands-on experience using Terraform for infrastructure provisioning, paired with robust CI/CD experience using GitHub Actions, Azure DevOps, or equivalent.
- Proven ability to rapidly audit, take over, and operate an existing data platform built by a third-party vendor.
- Upper-intermediate English level.
Nice to haves
- Experience with Power BI, including building or supporting semantic models and paginated reports.
- Healthcare domain knowledge, including familiarity with dental, medical, or HIPAA-regulated data environments.
- Experience with Azure VNet integration, including configuring virtual network peering, service endpoints, or VNet-injected resources.
Perks
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location
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Hiring process timeline
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A quick note
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Tell us about yourself
Submit a short application form.
Pass a quick test
Pass a 30’- 60’ test.
Record a short video
Introduce yourself on video to fast-track your application process.
Meet our team
Once you pass the video review, grab a spot on our calendar for a technical interview.
Get an offer
Welcome to AgileEngine!
Have any questions?
What is the work format and schedule?
We are a remote-first company, so all our positions are remote. Schedules are flexible, but the main requirement is to have an overlap with your client’s schedule to ensure smooth collaboration. Specific details depend on the project and are discussed during the interview process.
What level of English is required?
We look for Upper-Intermediate (B2) proficiency or higher. Since you will be collaborating with international teams and global clients (including Fortune 500 companies), English is a part of your daily work.
Does AgileEngine provide work equipment?
It depends on your location. We provide equipment in Ukraine, Poland, Argentina, Colombia, Mexico, Brazil, Guatemala, Portugal, Spain, and India. In the USA, equipment is usually provided by the client; otherwise, you will be expected to use your own setup.
What opportunities for professional growth do you offer?
We support continuous growth through personalized development paths tailored to each expert. Also, you can expect:
- An annual learning and development budget
- Internal workshops, tech talks, and mentorship programs
- Opportunities to switch projects or grow into new roles over time
What does a typical team look like, and what tools do you use?
Teams vary by project, but you’ll usually work with a mix of experts across different fields, along with a delivery or project manager who supports collaboration and onboarding.
For day-to-day work, teams commonly use tools like Jira and Google Workspace, along with communication platforms such as Google Chat. Depending on the client, you may also work with Slack, Confluence, Notion, or similar tools.
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