AgileEngine is an Inc. **** 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.
Data Engineer (Marketing-oriented) | Remote for Marketing Agency for Education
Our client is a fast-growing performance marketing agency specializing in mission-driven organizations across higher education and nonprofit sectors.
Since launching in ****, the agency has built a strong reputation for combining strategic thinking, creative execution, and data-driven marketing to help universities and organizations achieve measurable growth.
Company Overview
Our client is a fast-growing performance marketing agency specializing in mission-driven organizations across higher education and nonprofit sectors.
Since launching in ****, the agency has built a strong reputation for combining strategic thinking, creative execution, and data-driven marketing to help universities and organizations achieve measurable growth.
Your Role
The Senior Data Engineer sits at the center of the agency's Data and Analytics function, connecting every paid media platform and CRM the agency touches into a single, reliable source of truth.
You'll own the full path data takes: from a client's ad accounts and CRM, through Adverity, into a BigQuery warehouse, through modular dbt/Dataform transformations, and out to the Looker Studio dashboards and automated Google Sheets reports the team and its partners rely on daily.
Reporting to the Data and Analytics Manager, you're joining at a pivotal moment - the agency is scaling its roster of education and nonprofit partners, and this role is instrumental in evolving the automated reporting suite that makes that growth possible without sacrificing data quality or client trust.
You'll
Own data ingestion & pipeline architecture - connect and maintain API pipelines from paid media platforms (Meta, Google Ads, LinkedIn, TikTok, programmatic) into Adverity,



build custom Python connectors for anything not natively supported, and architect scalable pipelines from source system through to dashboard
Own CRM integration - build and maintain reliable CRM data connections (Slate, Salesforce, HubSpot) so lead and enrollment data flows cleanly into the warehouse
Own the data warehouse - route, optimize, and store raw and processed data in Google BigQuery; design efficient schemas for complex, multi-source marketing data (granularity, normalization, slowly changing dimensions); manage partitioning, clustering, and storage strategy to control query cost and performance
Own transformation & mapping - build SQL schemas that map, blend, and organize multi-channel data accurately for each client, in modular, version-controlled, documented dbt or Dataform pipelines, with standardized naming conventions and metric definitions across platforms and clients
Own CI/CD & data segregation - maintain CI/CD pipelines (GitHub Actions, automated testing) for robust, version-controlled releases, and enforce strict data segregation across multi-client environments
Enable the reporting layer - create clean, performant data views built specifically for fast Looker Studio dashboards and automated Google Sheets reports, and partner with the Data and Analytics Manager and client teams to translate reporting requirements into warehouse models
Drive data quality - monitor pipeline health, resolve API breaks, minimize latency, implement validation frameworks and automated testing, troubleshoot discrepancies to root cause across source/warehouse/BI layers, and proactively flag data quality risks to leadership
You Bring
5+ years of hands-on data engineering experience, ideally in a marketing or agency environment
Strong experience configuring datastreams, transformations, and destinations in Adverity or a comparable ETL platform (Fivetran, Supermetrics, Funnel)
Intermediate to advanced SQL, with proven BigQuery experience in transformation, partitioning, and modeling
Expertise in dbt or Dataform, managing modular, version-controlled, documented SQL transformation pipelines
Python proficiency for custom API connections and pipeline automation
Experience with CRM data flows and integrations (Slate, Salesforce, and/or HubSpot)
A deep understanding of marketing metrics (ROAS, CPA, CAC) and paid platform schemas, with a proven track record of structuring data to optimize Looker Studio performance
Proficiency with Git and collaborative development workflows, and proven ability to manage multi-client data environments with strict data segregation
An analytical, solution-driven mindset with a growth orientation, and strong communication skills that turn complex data workflows into clear narratives for non-technical audiences - education marketing experience (traditional or online) is especially valued
Bonus Points
Experience integrating AI-driven insights or machine learning models into marketing data pipelines to sharpen predictive analytics and data utility
Familiarity using AI or LLM tools to optimize performance forecasting, automated audience segmentation, or marketing workflows
Experience connecting, managing, and maintaining APIs for generative AI platforms within a marketing data architecture
Experience using AI/ML-driven anomaly detection to monitor pipelines and proactively flag data quality issues
What's Offered
Remote role with the flexibility that comes with a distributed, async-friendly team
Competitive compensation based on experience and location
A pivotal, high-visibility seat on a scaling Data & Analytics team, with real ownership over the agency's reporting infrastructure
The chance to build the data backbone for an agency whose partners are education and nonprofit organizations working to build a better world
A culture built around finding a better way, playing as a team of A-players, and treating results as the engine rather than the goal
Direct impact: the pipelines and models you build directly shape how partners see (and trust) their own performance data
Interview Process
Application Review (resume + a few questions)
Screening Call with Atomic HR
Hiring Team Interview (walkthrough of a pipeline or data model you've built)
Technical Assessment (a real-world data engineering case study)
Final Interview with company leadership
#J-*****-Ljbffr

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