Senior Data EngineerLuna Data Solutions, Inc. • Austin, TX, United States
Senior Data Engineer
Luna Data Solutions, Inc. • Austin, TX, United States
[job_card.variable_days_ago]
[job_preview.job_type]
- [job_card.full_time]
[job_card.job_description]Develop and maintain ETL / ELT pipelines using Azure Data Factory, Synapse Pipelines, and Databricks for both batch and streaming workloads. Integrate diverse data sources (on-prem, cloud, SaaS, APIs) into a unified Azure data environment. Optimize pipelines for cost-effectiveness, performance, and scalability. Implement MDM solutions using Azure-native or third-party platforms (e.g., Profisee, Informatica, Semarchy). Define and manage data governance, metadata, and data quality frameworks. Partner with business teams to align data standards and maintain data integrity across domains. Build and manage APIs for data access, transformation, and system integration using Azure API Management and Logic Apps. Design secure, reliable data services for internal and external consumers. Automate workflows and system integrations using Azure Functions, Logic Apps, and Power Automate. Perform core DBA tasks, including performance tuning, query optimization, indexing, and backup / recovery for Azure SQL and Synapse. Monitor and optimize cost, performance, and scalability across Azure data services. Implement CI / CD and Infrastructure-as-Code (IaC) solutions using Azure DevOps, Terraform, or Bicep. Work closely with data scientists, analysts, business stakeholders, and application teams to deliver high-value data solutions. Mentor junior engineers and define best practices for coding, data modeling, and solution design. Contribute to enterprise-wide data strategy and roadmap development. Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related fields. 5+ years of hands-on experience in Azure-based data engineering and architecture. Strong proficiency with the following : Azure Data Factory, Azure Synapse, Azure Databricks, Azure Data Lake Storage Gen2 SQL, Python, PySpark, PowerShell Azure API Management and Logic Apps Solid understanding of data modeling approaches (3NF, dimensional modeling, Data Vault, star / snowflake schemas). Proven experience with Lakehouse / medallion architectures and data mesh / data hub designs. Familiarity with MDM concepts, data governance frameworks, and metadata management. Experience with automation, data-focused CI / CD, and IaC. Thorough understanding of Azure security, RBAC, Key Vault, and core networking principles. Competitive compensation and benefits package Luna Data Solutions, Inc. (LDS) provides equal employment opportunities to all employees. All applicants will be considered for employment. LDS prohibits discrimination and harassment of any type regarding age, race, color, religion, sexual orientation, gender identity, sex, national origin, genetics, protected veteran status, and / or disability status.
We are looking for a seasoned Azure Data Engineer to design, build, and optimize secure, scalable, and high-performance data solutions within the Microsoft Azure ecosystem. This will be a multi-year contract worked FULLY ONSITE in Austin, TX.
The ideal candidate brings deep technical expertise in data architecture, ETL / ELT engineering, data integration, and governance, along with hands-on experience in MDM, API Management, Lakehouse architectures, and data mesh or data hub frameworks. This position combines strategic architectural planning with practical, hands-on implementation, empowering cross-functional teams to leverage data as a key organizational asset.
Key Responsibilities
1. Data Architecture & Strategy
- Design and deploy end-to-end Azure data platforms using Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Azure SQL Database.
- Build and implement Lakehouse and medallion (Bronze / Silver / Gold) architectures for scalable and modular data processing.
- Define and support data mesh and data hub patterns to promote domain-driven design and federated governance.
- Establish standards for conceptual, logical, and physical data modeling across data warehouse and data lake environments.
2. Data Integration & Pipeline Development
3. Master Data Management (MDM) & Data Governance
4. API Management & Integration
5. Database & Platform Administration
6. Collaboration & Leadership
Required Qualifications
What We Offer
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