AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Senior Data Engineer to operate and improve a Snowflake-based enterprise data platform in a regulated healthcare environment.

MUST HAVES

- 5+ years of professional experience in Data Engineering or Data Platform Engineering.
- Strong hands-on experience operating and developing solutions on Snowflake , including data-layer design, warehouse performance, access patterns, and production troubleshooting.
- Advanced SQL skills and strong experience with dbt for transformation, testing, documentation, lineage, and controlled deployment.
- Experience operating managed ingestion tools such as Fivetran or HVR and supporting custom data‑ingestion pipelines.
- Hands‑on experience with AWS data services , particularly S3 and event‑driven or file‑based ingestion patterns.
- Experience orchestrating and troubleshooting data workloads with Argo Workflows on Kubernetes , or comparable workflow‑orchestration technologies.
- Proficiency in Python or a comparable language for data engineering, automation, and operational tooling.
- Strong understanding of data modeling, pipeline dependencies, schema evolution, backfills, data validation, and production data quality.
- Experience with observability, logging, alerting, and incident‑management practices for production data platforms.
- Demonstrated ability to lead complex incident resolution, perform root‑cause analysis, and convert findings into preventive improvements.
- Ability to make well‑reasoned technical decisions, identify tradeoffs, estimate work, and guide improvements across a complex platform.
- Experience mentoring engineers and collaborating effectively with Cloud / DevOps, Analytics, Security, Governance, and business stakeholders.
- Strong written and verbal English communication skills, with the ability to work directly with client stakeholders.
- Full availability to work from 9:00 AM to 6:00 PM Pacific Time and participate in an agreed on‑call rotation.

NICE TO HAVES

- Hands‑on experience with a data‑specific observability platform.
- Experience supporting Tableau Cloud administration, data‑source connectivity, extracts, scheduled refreshes, or production dashboard dependencies.
- Familiarity with Snowflake cost optimization, audit logging, tasks, stored procedures, and environment rationalization.
- Experience migrating legacy ingestion or orchestration patterns such as Boomi or AWS Data Pipeline to modern managed or Kubernetes‑based solutions.
- Experience with Terraform, CI/CD pipelines, and Infrastructure as Code practices supporting data platforms.
- Experience with service‑management and change‑control tools such as Freshservice and Jira.
- Familiarity with HIPAA, GDPR, FDA‑related controls, least‑privilege access, separation of duties, and audit‑ready operational practices.

WHAT YOU WILL DO

- Provide senior technical ownership for the Data Platform service tower during the LatAm coverage window, including day‑to‑day operations, complex troubleshooting, and L2/L3 escalation.
- Operate and improve Snowflake production and non‑production environments, including warehouse configuration and sizing, performance and consumption monitoring, object lifecycle, environment hygiene, and support for production changes.
- Administer data access within established controls, including users, roles, service accounts, secrets, and credential rotation, while maintaining least‑privilege and audit‑ready practices.
- Operate and improve data ingestion across Fivetran, HVR where applicable, and custom pipelines, including connector configuration, scheduling, source onboarding, schema‑change coordination, failure recovery, backfills, and dependency management.
- Design, build, and maintain reliable pipelines and dbt models across RAW, CURATED, and CONSUMPTION layers, with appropriate testing, documentation, lineage, version control, and CI/CD practices.
- Support AWS S3 data‑lake operations, including raw and landing‑zone workflows, lifecycle and retention controls, access patterns, logging,



ingestion failures, and coordination with downstream Snowflake workloads.
- Support Argo Workflows and Kubernetes‑hosted data workloads in close coordination with the Cloud / DevOps team, including scheduling, troubleshooting, deployment, recovery, and capacity dependencies.
- Define and improve data quality and observability standards, including freshness, zero‑row, row‑count growth, null, duplicate, schema‑drift, and referential‑integrity checks.
- Expand end‑to‑end monitoring and lineage using tools such as SYNQ, dbt, Snowflake audit data, Splunk, and the agreed alerting stack, linking actionable alerts to evidence and runbooks.
- Lead or support major data incidents, root‑cause analysis, post‑incident reviews, and preventive actions across ingestion, orchestration, Snowflake, and downstream Tableau dependencies.
- Support Tableau Cloud operations where upstream data, connectivity, permissions, extracts, or refresh failures require Data Platform investigation.
- Identify and deliver standardization, automation, reliability, performance, and cost improvements, including migration of suitable legacy or custom extraction patterns toward agreed golden paths.
- Execute work through controlled incident, request, access, change, and release processes using established service‑management workflows.
- Create and maintain runbooks, operating procedures, architecture context, ownership information, recovery procedures, and knowledge‑transfer materials.
- Mentor Middle‑level engineers, review technical work, improve team practices, and ensure effective handoffs across the distributed service team.
- Participate in the Data Platform on‑call rotation for critical incidents outside staffed service hours.

PERKS AND BENEFITS

- Professional growth : Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation : USD‑based pay with education, fitness, and team activity budgets.
- Exciting projects : Modern solutions with Fortune 500 and top product companies.
- Flextime : Adaptable schedule with remote and office options.

Strategy & Consulting | Data Engineering Consulting Practitioner - Process Mining

Hoy

In Accenture, within the Strategy & Consulting – Global Network area, we work with leading global clients to design and implement strategies that drive transformation and sustainable growth. As part of our team, you will collaborate on projects that combine innovation, deep analysis, and strategic execution, helping organizations tackle their most complex challenges. As a part of our Supply Chain & Engineering practice, you will help organizations reimagine and transform their supply chains for tomorrow—with a positive impact on the business, society and the planet. Together, let’s innovate, build competitive advantage, and improve business, and societal outcomes, in an ever‑changing, ever‑challenging world. Help us make supply chains work better, faster, and be more resilient, with the following initiatives:

- Be the process architect to lead process discovery and whiteboarding sessions with senior business stakeholders.
- Deliver process discovery or improvement projects using process mining tools.
- Work on process mining market leaders like Celonis, Signavio, Power automate Process Mining, and so on.
- Develop business requirements for the implementation of technology solutions for the client.
- Demonstrate in‑depth knowledge of industry trends , SAP transformation journey, new technologies, and tools.
- Aid in asset, accelerator, use case creation and enhancement
- Contribute to business development initiatives and display ability to solve complex business problems

Why AgileEngine‑Mid‑level Data Engineer

We are looking for a Mid‑level Data Engineer to build and maintain dbt pipelines and Snowflake data marts behind customer‑facing reporting, spend analytics, and AI features.

The mandatory requirements are solid dbt experience (modeling, tests, macros, and incremental models), ingestion and orchestration tools such as Airbyte or Prefect,



3+ years in data or analytics engineering on production pipelines, strong SQL and Python, dimensional modeling, Snowflake or a similar cloud warehouse, and an upper‑intermediate English level.

WHAT YOU WILL DO

- Build and maintain the dbt pipelines, data marts, and warehouse models that serve in‑app reporting, spend analytics, AI features, and internal analytics, treating them as production systems.
- Translate complicated procurement business logic into maintainable, well‑tested pipeline code, and notice when a model is valid‑looking but wrong.
- Build models within our data mart architecture, following the chapter's conventions for grain, conformed dimensions, and incremental patterns, and propose improvements when you find them.
- Contribute to and help buildout the semantic layer that our internal MCP servers and AI agents query, so that metrics and dimensions are defined once and answered consistently.
- Maintain the boundary between PII and agent/reporting‑safe data.
- Build and maintain the FastAPI services that expose reporting marts to customers.
- Build and maintain ingestion pipelines (Airbyte, OneSchema, S3) into the warehouse, and support our Forward Deployed Engineering function in bringing customer data into our systems.
- Implement data quality checks: freshness, schema and reconciliation tests, and alerting, so problems surface before customers find them.
- Implement metric definitions faithfully, and flag conflicting or ambiguous definitions to the chapter rather than guessing.
- Keep documentation and lineage current so that humans and AI agents can both find and trust what's in the warehouse.
- Tune Snowflake performance and cost within the models you build.
- Use agentic coding tools in your daily work, within the guardrails (tests, conventions, review patterns) the team maintains, and understand why those guardrails exist.
- Share what you learn through code review and team discussion.
- Communicate clearly with engineering, product, and customer‑facing teams about what the data means and what it can and can’t do.

MUST HAVES

- 3+ years in analytics engineering, data engineering, or a closely related role, including hands‑on work on production data pipelines that other systems or customers depended on.
- Solid dbt experience: modeling, tests, macros, and incremental models.
- Strong SQL and working Python.
- Data modeling fundamentals: dimensional modeling, data marts, grain and conformance.
- Experience with a modern cloud warehouse (Snowflake preferred).
- Experience with ingestion tooling and orchestration (Airbyte, Prefect, or equivalents).
- Familiarity with agentic coding tools and an understanding of why guardrails around their output matter.
- Deep curiosity about the business: you want to understand what the data means and how customers use it, not just how it flows.
- Software engineering discipline for analytics code: Git, code review, CI/CD.
- Can take a multi‑sprint piece of work from spec to production with normal oversight, and can explain tradeoffs to technical and non‑technical stakeholders.
- Upper‑intermediate English level.

NICE TO HAVES

- Experience building or maintaining API services on top of warehouse data (FastAPI or similar).
- Experience with a semantic layer or governed metric definitions that multiple consumers rely on, including for LLM‑driven or agent‑driven querying.
- Experience exposing warehouse data to customers through embedded analytics or customer‑facing APIs.
- Experience with data observability tooling.
- Experience supporting customer data onboarding or implementation teams.
- Experience deploying data pipelines across multiple regions and managing PII or sensitive data.
- Knowledge of procurement and/or supply chain data models.
- Prior experience in enterprise software and startups.

PERKS AND BENEFITS

- Professional growth : Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation : USD‑based pay with education, fitness, and team activity budgets.
- Exciting projects : Modern solutions with Fortune 500 and top product companies.
- Flextime : Flexible schedule with remote and office options.

Job Description

AgileEngine is an Inc. 5000 company that creates award‑winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people‑first culture has earned us multiple Best Place to Work awards.

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