VaultSpeed Data Engineer

Eliassen Group
Lansing, United States of America
yesterday

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 177K

Job location

Remote
Lansing, United States of America

Tech stack

API
Airflow
Azure
Cloud Storage
Code Generation
Information Systems
Databases
Continuous Integration
Directed Acyclic Graph (Directed Graphs)
Data Validation
Information Engineering
Data Infrastructure
Data Integration
ETL
Data Systems
Data Vault Modeling
Relational Databases
Python
Operational Data Store
Operational Databases
Reference Data
Cloud Services
Azure
Software Engineering
SQL Databases
Enterprise Data Management
Data Logging
Enterprise Software Applications
Azure
Spark
Change Data Capture
GIT
Microsoft Fabric
Data Lake
PySpark
Information Technology
Data Lineage
Kafka
REST
Terraform
Software Version Control
Data Pipelines
Databricks

Job description

  • Own the technical implementation and ongoing support of VaultSpeed.
  • Configure and maintain source-system metadata within VaultSpeed.
  • Design and maintain Raw Vault, Business Vault, and downstream data models.
  • Develop and maintain Data Vault 2.0 hubs, links, satellites, reference structures, and historization patterns.
  • Configure VaultSpeed mappings, parameters, templates, releases, and generated code.
  • Review, troubleshoot, and optimize VaultSpeed-generated SQL and loading processes.
  • Manage VaultSpeed releases and promote generated data solutions across development, QA, UAT, and production environments.
  • Integrate VaultSpeed-generated workloads with Astronomer and Apache Airflow.
  • Develop, maintain, and troubleshoot Airflow DAGs, tasks, dependencies, schedules, retries, alerts, and deployment configurations.
  • Develop and support Azure Data Factory pipelines, linked services, datasets, triggers, integration runtimes, and parameterized workflows.
  • Design reliable batch, incremental, change-data-capture, and event-driven data pipelines.
  • Integrate data from ERP, CRM, manufacturing, finance, operational databases, APIs, files, and cloud services.
  • Monitor pipeline execution, investigate failures, perform root-cause analysis, and implement permanent corrective actions.
  • Implement data validation, reconciliation, observability, lineage, auditing, and data-quality controls.
  • Improve pipeline performance, recoverability, scalability, and operational supportability.
  • Establish reusable pipeline patterns, coding standards, documentation, and deployment practices.
  • Implement source control and CI/CD practices for VaultSpeed, Airflow, ADF, SQL, and related configuration.
  • Work with data architects, analysts, application teams, infrastructure, security, and business stakeholders.
  • Document source-to-target mappings, data lineage, transformation logic, operational procedures, and support runbooks.
  • Mentor other data engineers and transfer VaultSpeed knowledge to the internal team.
  • Participate in the technical evaluation and potential adoption of Databricks.

Requirements

Our client is seeking a Senior Data Engineer with hands-on VaultSpeed experience to support and improve the enterprise data integration platform. The role focuses on developing, maintaining, troubleshooting, and optimizing data pipelines across VaultSpeed, Astronomer or Apache Airflow, and Azure Data Factory. The immediate priority is strengthening the current VaultSpeed implementation, improving pipeline reliability, and helping the team establish repeatable data-engineering standards. The role will also participate in evaluating and potentially transitioning portions of the data platform to Databricks. Databricks experience is preferred but is not a substitute for required VaultSpeed expertise.

This is a contract to hire opportunity. Applicants must be willing and able to work on a w2 basis and convert to FTE following contract duration. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance., * Five or more years of professional data-engineering, data-integration, or data-warehouse development experience.

  • Demonstrated hands-on production experience with VaultSpeed.
  • Ability to independently configure, develop, deploy, troubleshoot, and support VaultSpeed solutions.
  • Strong understanding of Data Vault 2.0 concepts and implementation practices.
  • Experience building and maintaining enterprise ETL and ELT pipelines.
  • Strong experience with Astronomer or production Apache Airflow environments.
  • Experience developing Airflow DAGs using Python.
  • Strong experience with Azure Data Factory.
  • Advanced SQL development and troubleshooting skills.
  • Experience with relational databases and enterprise data warehouses.
  • Experience with incremental loading, change data capture, historization, late-arriving data, and data reconciliation.
  • Experience integrating databases, REST APIs, files, cloud storage, and enterprise applications.
  • Experience diagnosing pipeline failures and resolving data, code, configuration, infrastructure, and dependency issues.
  • Experience implementing pipeline monitoring, logging, alerting, retry, and recovery mechanisms.
  • Experience using Git-based source control and CI/CD deployment processes.
  • Strong technical documentation and communication skills.
  • Ability to work directly with business and technical teams to translate data requirements into maintainable solutions.
  • Required VaultSpeed capabilities: source metadata harvesting and management, Data Vault model generation, Raw and Business Vault implementation, business keys, hubs, links, satellites, reference data, historization, source-to-target mappings and business-rule configuration, parameters and code-generation settings, release lifecycle, generated DDL and ELT code, integration with Airflow or ADF, troubleshooting generated SQL and orchestration, templates and deployment patterns, APIs or SDK, data lineage and impact analysis.
  • Preferred: Databricks, Apache Spark or PySpark, Delta Lake, Lakeflow, Unity Catalog, dbt, Azure Data Lake Storage Gen2, Kafka, Terraform, Azure DevOps, Microsoft Purview, and experience with manufacturing, ERP, finance, supply-chain, or operational data.

Education Requirements:

Bachelor's degree in computer science, data engineering, information systems, software engineering, or a related discipline is preferred. Equivalent professional experience will be considered in place of a degree.

Benefits & conditions

Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range.

W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick time if required by law in the worked-in state/locality.

If anyone reaches out to you about an open position connected with Eliassen Group, please ensure that you are working directly with us by confirming the following:

· When you work with Eliassen Group, all email communication will come from an Eliassen.com address, never Gmail, Yahoo, etc.

About the company

Eliassen Group is a strategic consulting firm that helps organizations reach further and achieve more through our technology, business advisory, and life sciences solutions. For nearly 40 years, we have combined exceptional people, deep domain expertise, and intelligent capabilities to expand our clients' capacity and accelerate meaningful outcomes. We are driven by a purpose to positively impact the lives of our employees, clients, consultants, and the communities we serve.

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