Senior Data Engineer

DataJobs

Austin (TX)

Hybrid

USD 103,000 - 117,000

Full time

5 days ago

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Job summary

RHL Technologies in Austin, TX is hiring a Senior Data Engineer to design and modernize enterprise cloud data platform capabilities on Azure.

You will build scalable data pipelines using Azure Databricks, PySpark, SQL, and Delta Lake, implementing Bronze/Silver/Gold patterns for reporting, analytics and AI. You will lead design reviews, mentor engineers, and promote security, governance, and cost-conscious practices to deliver reliable production solutions.

Qualifications

10+ years experience in data engineering, data warehousing, or data platform engineering.
5+ years designing cloud-based data warehouse or data lake solutions.
3+ years hands-on Azure Databricks in enterprise production environments.
Experience leading technical implementations and production releases.
Experience in regulated environments preferred.

Responsibilities

Design, develop, and maintain scalable data pipelines and data products.
Implement Bronze, Silver, and Gold architecture patterns for enterprise analytics.
Lead technical reviews and guide production implementation.
Develop and support batch, near-real-time, and streaming integration solutions.
Mentor engineers and promote coding standards.

Skills

SQL

Python

PySpark

Azure Databricks

Delta Lake

Unity Catalog

Databricks Workflows

Delta Live Tables

RBAC

Power BI

Data governance

Data quality

Mentoring

Education

Bachelor's degree

Master's degree preferred

Tools

Azure DevOps

Git CI/CD

Databricks Asset Bundles

Job description

RHL Technologies is hiring a Senior Data Engineer to design and modernize enterprise cloud data platform capabilities on Azure.

Responsibilities

Design, develop, and maintain scalable data pipelines, ingestion frameworks, transformation processes, and reusable data products using Azure Databricks, PySpark, SQL, and Delta Lake.
Implement Bronze, Silver, and Gold architecture patterns for enterprise reporting, analytics, AI, and self-service consumption.
Build reusable frameworks, utilities, and platform components to improve engineering productivity, quality, consistency, and deployment speed.
Develop and support batch, near-real-time, and streaming integration solutions, including modernization of legacy warehouse and ETL workloads.
Act as technical lead for complex initiatives: create solution designs, lead technical reviews, recommend tools and approaches, and guide production implementation.
Partner with data architects and platform leaders to deliver scalable, secure, governed, cost-conscious solutions that are operationally supportable.
Mentor engineers and promote standards for coding, testing, documentation, performance, and production readiness.
Implement data quality, validation, reconciliation, monitoring, metadata, and lineage; support RBAC and enterprise security controls.
Build and maintain CI/CD, automated testing, deployment, and release processes using Azure DevOps and Git-based practices.
Contribute to platform observability including alerting, operational dashboards, health metrics, performance tuning, and cost optimization.
Participate in production support, incident response, pager, and on-call rotations; troubleshoot issues, lead root cause analysis, and implement durable remediation.
Create and maintain operational runbooks, support procedures, technical documentation, and knowledge-sharing assets.
Collaborate with architecture, governance, security, analytics, application, and business teams to translate requirements into platform solutions.
Support technical discovery, estimation, roadmap planning, delivery execution, and evaluation of emerging cloud, data, and AI capabilities.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related field.
Master’s degree preferred.
10+ years of experience in data engineering, data warehousing, or data platform engineering.
5+ years designing or implementing cloud-based data warehouse, data lake, or data platform solutions.
3+ years of hands‑on Azure Databricks experience in enterprise production environments.
Experience with ETL/ELT, data modeling, large-scale integration, and cloud platform modernization.
Experience leading technical implementations, solution design, design reviews, and production releases.
Experience supporting production environments including incident response, root cause analysis, and operational support processes.
Experience in regulated environments (financial services, banking, or audit-sensitive) preferred.

Technology

Azure Databricks
PySpark
SQL
Delta Lake
Bronze, Silver, Gold
ETL, ELT
Azure DevOps
Git-based practices
Unity Catalog
Databricks Workflows
Delta Live Tables
RBAC
Power BI
MicroStrategy
MDM

Skills & Competencies

Advanced proficiency in SQL, Python, PySpark, and Spark performance optimization.
Strong experience with Azure Databricks, Delta Lake, Unity Catalog, Databricks Workflows, and Delta Live Tables.
Strong understanding of lakehouse, Medallion Architecture, dimensional modeling, data warehousing, and analytics-oriented structures.
Experience with Azure DevOps, Git CI/CD, automated testing, and deployment practices; Databricks Asset Bundles experience preferred.
Experience implementing data quality, validation, reconciliation, monitoring, metadata, lineage, governance, and security controls.
Strong technical leadership, solution design, analytical, troubleshooting, and problem-solving skills.
Ability to lead complex work end-to-end while balancing innovation with reliability, security, cost, and supportability.
Excellent collaboration, mentoring, documentation, and communication across technical and business teams.
Experience with Power BI, MicroStrategy, MDM, streaming architectures, infrastructure automation, or AI-assisted development preferred.
Databricks Data Engineer certification (Associate or Professional) preferred.