azure data engineer

IT America Inc

Data Engineer (Databricks)Azure Databricks EnvironmentAustin, TX - HybridGeneral InformationDescription:The Databricks Data and AI Agent Automation Engineer is responsible for designing, developing, and deploying intelligent agents that automate data engineering development (dev) and quality assurance (QA) tasks within the Azure Databricks environment. This role bridges software engineering and data platform operations, leveraging AI/ML capabilities, prompt engineering, and low-code/no-code automation frameworks to accelerate platform development cycles, reduce manual toil, and improve code quality. The engineer will work closely with the Data Platform team to build, test, and operationalize agents that enhance developer productivity, streamline CI/CD pipelines, and automate governance and compliance checks.Responsibilities&middot; Design and implement intelligent agents (LLM-powered, rule-based, or hybrid) that automate data engineering workflows in Azure Databricks&middot; Develop agents for automated code generation, refactoring, and optimization of PySpark and SQL workloads&middot; Build agents that automate data quality validation, testing, and reconciliation tasks in dev and QA environments&middot; Create agents for metadata management, lineage tracking, and governance automation within Databricks&middot; Develop autonomous CI/CD pipeline tasks, including automated test case generation, deployment validation, and rollback logic&middot; Implement agents that perform intelligent monitoring, anomaly detection, and root-cause analysis for data pipelines&middot; Build prompt engineering frameworks and agent orchestration patterns tailored to data engineering use cases&middot; Collaborate with data engineers and architects to identify high-impact automation opportunities and prioritize agent development roadmap&middot; Establish best practices for agent development, testing, deployment, and observability within Azure Databricks&middot; Document agent workflows, decision logic, and operational runbooks for team knowledge sharing&middot; Evaluate emerging AI/agent frameworks and technologies; recommend adoption where applicableJob RequirementsEducation&middot; Bachelor's degree in Computer Science, Software Engineering, Data Science, or related field (Master's preferred)Experience&middot; 5+ years of data engineering or software engineering experience, with hands-on work in cloud data platforms (Databricks, Snowflake, Azure)&middot; Proven experience developing automation solutions, agents, or AI-powered tools (e.g., using LLMs, prompt engineering, or orchestration frameworks like Databricks Agent Framework (or LangChain, AutoGen)&middot; Strong proficiency in Python and SQL with focus on production-grade code quality&middot; Demonstrated experience with Azure Databricks (notebooks, jobs, workflows, DLT) or equivalent modern data platforms&middot; Hands-on experience with CI/CD/CT tools (GitHub Actions, Azure DevOps Pipelines) and automation frameworks&middot; Experience building data quality frameworks, testing patterns, or QA automation&middot; Prior work in regulated or risk-sensitive environments preferredSkills &amp; Competencies&middot; Expert-level Python programming with strong software engineering practices (testing, documentation, version control)&middot; Strong SQL and PySpark optimization skills&middot; Hands-on experience with LLM APIs, prompt engineering, and AI agent frameworks (e.g., Databricks Agent Bricks, LangChain, OpenAI, Azure OpenAI)&middot; Proficiency in Azure Databricks, including Delta Lake, workflows, and Databricks Asset Bundles&middot; Experience designing and implementing automation workflows using orchestration tools or serverless platforms&middot; Strong problem-solving and systems thinking skills; ability to decompose complex workflows into automatable components&middot; Excellent communication and documentation skills; ability to articulate technical concepts and agent design rationale&middot; Self-directed learner with curiosity about emerging AI/automation technologies&middot; Ability to collaborate effectively with cross-functional teams (data engineers, architects, QA, operations)Pay: $65.00 - $70.00 per hourWork Location: Hybrid remote in Austin, TX 78701

Azure Data Engineer

VeeRteq Solutions Inc.

<div>Role:Azure Data / Search Engineer (Databricks / ElasticSearch / Python)
Experience: - Min8+ Years
Location: - Irving, TX (Hybrid 3 days Work from Office)
Looking for a strong Azure Data Engineer / Senior Software Engineer with strong expertise in Python, Databricks, SQL, Elasticsearch, Kafka, and Azure, responsible for building scalable search platforms, REST APIs, event-driven data pipelines, and cloud-native distributed systems supporting high-volume enterprise applications.
Roles and Responsibilities: -
Resource will be responsible to design, build, and support client, our enterprise search and intelligent matching platform.
This role will develop scalable APIs, high-performance search capabilities, event-driven data pipelines, and cloud-native services supporting millions of transactions daily.
The consultant will work across Azure, Elasticsearch, Kafka, Databricks, Python, and distributed systems to build highly available, low-latency applications.
The ideal candidate has strong backend engineering experience with cloud-native architectures, search technologies, REST APIs, event streaming, and large-scale data processing.
Design and develop scalable backend services using Python. Build and maintain REST APIs supporting enterprise applications. Design and optimize Elasticsearch indexes, queries, mappings, and search relevance.
Develop intelligent search and matching capabilities for large-scale datasets. Build event-driven architectures using Kafka and Azure Event Hub. Design high-throughput data ingestion and indexing pipelines. Integrate applications with Databricks and enterprise data platforms.
Develop secure cloud-native applications on Microsoft Azure. Implement CI/CD pipelines and automated deployment processes.
Monitor application health, logging, observability, and production performance. Optimize API response time, indexing performance, and infrastructure utilization. Participate in architecture, design reviews, code reviews, and production support.
Collaborate with product managers, architects, data scientists, and engineering teams.
Educational Qualifications: -
Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
Technical certification in multiple technologies is desirable.
Skills: -
Mandatory skills
Programming Python (required) SQL REST APIs JSON FastAPI (preferred) Async Python Cloud Microsoft Azure Azure App Services Azure Linux VMs Azure Container Apps / AKS (preferred) Azure Managed Identity Azure Key Vault Azure Storage Azure Monitor Azure Event Hub Search
Technologies Elasticsearch Query DSL Relevance tuning Mapping design Aggregations Multi-search (msearch) Bulk indexing Search optimization Index lifecycle management Event Streaming Apache Kafka Confluent Cloud Producers / Consumers Kafka Connect Schema Registry
Event-driven architecture Data Engineering Databricks PySpark Delta Lake Data ingestion pipelines ETL/ELT DevOps Git Azure DevOps Azure Pipelines CI/CD Docker Infrastructure as Code (Terraform or Pulumi preferred) Databases PostgreSQL SQL Server Relational Databases Required
ExperienceMin 8+ years of software engineering experience. Strong Python backend development experience. Experience designing and operating production REST APIs.
Strong experience with Elasticsearch in production environments. Experience building scalable search platforms. Experience with Kafka or enterprise event-streaming platforms. Experience deploying applications on Microsoft Azure. Experience with CI/CD pipelines and automated deployments.
Experience troubleshooting production systems and performance issues. Strong understanding of distributed systems and microservices.
Preferred Qualifications:
Experience with AI-assisted search or intelligent matching platforms. Experience with Databricks and Delta Lake.
Experience with machine learning integration. Experience with semantic search or vector search.
Experience with Azure OpenAI or LLM integration. Healthcare or supply chain experience. Experience using GitHub Copilot or Codex.
VeeRteq Solutions is an Equal Opportunity Employer</div>

Azure Data / Search Engineer

EXL Service

<div>Job Description: EXL Service is seeking an accomplished Senior Databricks Data Engineer with 10&ndash;12 years of experience designing, developing, and optimizing enterprise data platforms and large-scale ETL solutions. The ideal candidate brings deep expertise in Databricks, Spark, Delta Lake, Azure Data Platform, and modern data engineering practices.
This role is responsible for building scalable data pipelines, implementing cloud-native data solutions, improving platform performance, and delivering reliable data products for analytics, reporting, and AI/ML initiatives.
Base Compensation Range: 65,000 &ndash; 87,000
The posted range is the hiring range for this role &mdash; a subset of the broader range available to employees over time &mdash; and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.
For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits</div>
 <div>Responsibilities: Key Responsibilities
Data Engineering &amp; Platform Development
<ul><li>Design, develop, and optimize enterprise-scale data pipelines using Databricks, Spark, Delta Lake, and Azure Data Lake Storage.
</li><li>Build batch and incremental ETL/ELT pipelines, real-time streaming architectures, and reusable data integration frameworks.
</li><li>Develop scalable ingestion frameworks supporting structured, semi-structured, and API-based data sources.
</li><li>Build reusable data engineering frameworks for ingestion, transformation, validation, reconciliation, and publishing.
</li><li>Develop Delta Lake solutions using partitioning, optimization, Z-Ordering, Liquid Clustering, and performance tuning techniques.
</li><li>Implement CDC, incremental processing, merge strategies, and data synchronization across enterprise platforms.
</li><li>Develop Databricks Workflows, notebooks, SQL Jobs, and automation for production workloads.
</li><li>Integrate external REST APIs and process JSON/XML data into analytics-ready datasets.
</li><li>Implement robust data quality checks, audit frameworks, monitoring, and error handling.
</li>Optimize Spark jobs for performance, scalability, and cost efficiency. 
<li>
</li></ul>Databricks &amp; Azure Development
<ul><li>Develop solutions using Azure Data Lake Storage Gen2, Databricks, Unity Catalog, Azure Key Vault, Azure DevOps, and Azure Synapse.
</li><li>Build secure data pipelines using Unity Catalog, RBAC, service principals, and managed identities.
</li><li>Develop reusable notebook frameworks using PySpark and Spark SQL.
</li><li>Implement CI/CD deployment pipelines using Azure DevOps.
</li><li>Manage environment promotion across Development, QA, UAT, and Production.
</li>Troubleshoot production issues and optimize workloads for reliability and scalability. 
<li>
</li></ul>Data Integration &amp; Analytics
<ul><li>Design enterprise data models supporting reporting, analytics, and downstream applications.
</li><li>Develop healthcare and financial data integration pipelines supporting multiple source systems.
</li><li>Build reusable metadata-driven ETL frameworks.
</li><li>Integrate third-party APIs including NLP, terminology normalization, and identity resolution services.
</li><li>Support data governance, lineage, and metadata management initiatives.</li></ul></div>
 <div>Qualifications: Required Skills &amp; Experience
Technical Expertise
<ul><li>10-12 years of experience in Data Engineering, ETL Development, and Data Warehousing.
</li><li>Hands-on Databricks development experience.
</li><li>Strong experience with Spark, Delta Lake, Unity Catalog, Databricks Workflows, and SQL Warehouses.
</li><li>Strong experience with PySpark, Spark SQL, SQL, and Python.
</li><li>Experience building enterprise ETL/ELT pipelines using Databricks and Azure Data Platform.
</li><li>Experience with Azure Data Lake Storage (ADLS Gen2), Azure Synapse, Azure Key Vault, and Azure DevOps.
</li><li>Experience implementing CDC, SCD, incremental loading, and data quality frameworks.
</li><li>Experience integrating REST APIs and processing JSON/XML datasets.
</li><li>Experience with Git, CI/CD, release management, and deployment automation.
</li><li>Strong knowledge of performance tuning, partitioning, caching, broadcast joins, and Spark optimization.
</li><li>Experience working with healthcare data platforms is preferred.
</li><li>Microsoft Azure certifications (e.g., DP-203 Azure Data Engineer Associate) or Databricks certifications (Data Engineer Associate/Professional).
</li><li>Experience with Ab Initio suite of products is also preferred.</li></ul></div>

Databricks Data Engineer

<div>
 Position Description
 
 
 Join a high performing data engineering team responsible for building modern, cloud native data platforms on Microsoft Azure. This role offers the opportunity to design and implement scalable, secure, and high performance data solutions using Azure Databricks, with a strong focus on Unity Catalog, data governance, and enterprise analytics within the Investment/Capital Markets domain.
 
 
 The ideal candidate is passionate about cloud data engineering, enjoys solving complex data challenges, and thrives in a collaborative Agile environment. This position provides the opportunity to work with the latest Azure data technologies while delivering impactful business solutions.
 
 
 Work Location: Onsite at the client location in Pittsburgh, PA.
 
 
 Your future duties and responsibilities
 
 
 <ul>
 <li>
 Design, develop, and maintain scalable data pipelines using Azure Databricks.
 </li>
 <li>
 Build and optimize ETL/ELT workflows leveraging PySpark, SQL, and Delta Lake.
 </li>
 <li>
 Implement and manage Unity Catalog to support enterprise data governance, security, metadata management, and fine-grained access control.
 </li>
 <li>
 Develop cloud native data engineering solutions on the Microsoft Azure platform.
 </li>
 <li>
 Collaborate with architects, business analysts, and cross functional teams to gather and translate business requirements into technical solutions.
 </li>
 <li>
 Optimize Spark jobs and data pipelines for performance, scalability, and cost efficiency.
 </li>
 <li>
 Ensure data quality, reliability, and compliance through validation, monitoring, and best practices.
 </li>
 <li>
 Support production deployments, troubleshooting, and performance tuning.
 </li>
 <li>
 Participate in code reviews, technical documentation, and continuous improvement initiatives.
 </li>
 <li>
 Apply best practices for cloud data engineering, security, and DevOps within Azure environments.
 
 
 </li>
 </ul>
 
 Required Qualifications To Be Successful In This Role
 
 
 
 <ul>
 <li>
 Minimum 5 years of hands-on experience with Azure Databricks.
 </li>
 <li>
 Hands on experience with Unity Catalog is mandatory.
 </li>
 <li>
 Strong experience building enterprise scale data engineering solutions on Microsoft Azure.
 </li>
 <li>
 Expert level experience with Apache Spark (PySpark) and SQL.
 </li>
 <li>
 Strong experience with Delta Lake, ETL/ELT development, and data pipeline implementation.
 </li>
 <li>
 Experience with Azure data services such as Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), and related Azure ecosystem services.
 </li>
 <li>
 Strong understanding of data governance, metadata management, security, and access control.
 </li>
 <li>
 Mandatory experience in the Investment/Capital Markets domain.
 </li>
 <li>
 Experience with Git and CI/CD practices.
 </li>
 <li>
 Excellent analytical, communication, and problem solving skills.
 </li>
 <li>
 Experience working in Agile/Scrum delivery environments.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Databricks Certified Data Engineer (Associate or Professional).
 </li>
 <li>
 Microsoft Azure Data Engineer Associate (DP 203) certification.
 </li>
 <li>
 Experience with Infrastructure as Code (Terraform/Bicep).
 </li>
 <li>
 Experience implementing DevOps practices for Azure Databricks environments.
 </li>
 <li>
 Familiarity with Azure Purview/Microsoft Purview is a plus.
 
 
 </li>
 </ul>
 CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. To support the ability to reward for merit-based performance, CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $79,600.00 $139,300.00.
 
 
 CGI's benefits are offered to eligible professionals on their first day of employment to include:
 
 
 <ul>
 <li>
 Competitive compensation
 </li>
 <li>
 Comprehensive insurance options
 </li>
 <li>
 Matching contributions through the 401(k) plan and the share purchase plan
 </li>
 <li>
 Paid time off for vacation, holidays, and sick time
 </li>
 <li>
 Paid parental leave
 </li>
 <li>
 Learning opportunities and tuition assistance
 </li>
 <li>
 Wellness and Well-being programs
 
 
 </li>
 </ul>
 
 Together, as owners, let&rsquo;s turn meaningful insights into action.
 
 
 
 Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you&rsquo;ll reach your full potential because&hellip;
 
 
 You are invited to be an owner from day 1 as we work together to bring our Dream to life. That&rsquo;s why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company&rsquo;s strategy and direction.
 
 
 Your work creates value. You&rsquo;ll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise.
 
 
 You&rsquo;ll shape your career by joining a company built to grow and last. You&rsquo;ll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.
 
 
 Come join our team&mdash;one of the largest IT and business consulting services firms in the world.
 
 
 Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business.
 
 
 CGI provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job in the U.S., please email the CGI U.S. Employment Compliance mailbox at US_Employment_Compliance@cgi.com. You will need to reference the Position ID of the position in which you are interested. Your message will be routed to the appropriate recruiter who will assist you.
 
 Please note, this email address is only to be used for those individuals who need an accommodation to apply for a job. Emails for any other reason or those that do not include a Position ID will not be returned.
 
 
 
 We make it easy to translate military experience and skills! Click here to be directed to our site that is dedicated to veterans and transitioning service members.
 
 
 All CGI offers of employment in the U.S. are contingent upon the ability to successfully complete a background investigation. Background investigation components can vary dependent upon specific assignment and/or level of US government security clearance held. Dependent upon role and/or federal government security clearance requirements, and in accordance with applicable laws, some background investigations may include a credit check. CGI will consider for employment qualified applicants with arrests and conviction records in accordance with all local regulations and ordinances.
 
 
 CGI will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with CGI&rsquo;s legal duty to furnish information.
 
 
</div>

Data Engineer - Databricks - Local to Pittsburgh, PA

Immersion Consulting, LLC

<div>Description:

The Senior Data Engineer is responsible for designing, implementing, maintaining, and optimizing a cloud-based data architecture and data pipeline ecosystem. The position supports advanced analytics, machine learning operations, fraud detection initiatives, and investigative activities by delivering scalable, secure, and sustainable Azure-based data solutions. The Senior Data Engineer develops and maintains modern ELT/ETL pipelines, data models, source-controlled environments, and operational standards that enable efficient data ingestion, processing, storage, and access.<ul><li>
Design, implement, and maintain scalable Azure-based data architecture supporting audits, investigations, and fraud analytics.</li><li>
Develop, optimize, and sustain ELT/ETL pipelines within Azure Synapse Analytics and Azure Machine Learning environments.</li><li>
Migrate and integrate large-scale datasets into Azure Data Lake Storage (ADLS).</li><li>
Establish source control, version management, and development standards across data engineering assets.</li><li>
Implement pipeline monitoring, validation, logging, and error-handling frameworks.</li><li>
Design and maintain data models, data dictionaries, entity relationship diagrams, and architectural documentation</li><li>
Optimize ingestion, transformation, storage, and retrieval performance across diverse data sources and formats.</li><li>
Develop self-service data access capabilities for analysts and investigators.</li><li>
Collaborate with Data Scientists to ensure infrastructure effectively supports machine learning and AI initiatives.</li><li>
Author and maintain Standard Operating Procedures (SOPs) governing data pipeline development, deployment, and monitoring.</li><li>
Evaluate emerging AI-enabled engineering tools and LLM-assisted automation capabilities.</li><li>
Recommend and implement architectural improvements that increase efficiency, reliability, security, and cost effectiveness.</li></ul>
Requirements:
<ul><li>Bachelor's degree in Data Engineering, Computer Science, Data Science, Machine Learning, Mathematics, or related discipline; or 5 years of relevant applied experience.</li><li>
Five or more years of experience maintaining SQL database environments and performing advanced SQL/T-SQL operations.</li><li>
Five or more years of experience designing and maintaining cloud-based ELT/ETL solutions.</li><li>
Three or more years of experience working with Azure Synapse Analytics and Azure Machine Learning.</li><li>
Three or more years of experience developing data solutions using Python and Pandas.</li><li>
Experience supporting modern data platforms and cloud-native analytics architectures.</li><li>
Demonstrated expertise in data architecture design, pipeline optimization, and operational support.</li></ul></div>

Senior Data Engineer

Howard Energy Partners

<div><div><div>At Howard Energy Partners, we believe that people build capability, capability drives performance, and performance, when guided by purpose, allows us to deliver energy that helps communities prosper. This role sits at the center of how we amplify that through data, automation, and the intelligent tools our teams will depend on for years to come.</div><div> 

</div><div>Raw data is everywhere: in our systems, our sensors, our transactions. But data alone doesn't move the business. It has to be shaped into information, refined into evidence, and ultimately owned as knowledge before it becomes something a person can act on. That journey, from source to decision, is what this team is responsible for, and why the work matters</div><div> 

</div><div>This is a hands-on engineering role on a small team. You will write code, ship pipelines, keep production healthy, and partner with people across Operations, IT, Finance, and the business to turn requirements into durable, reliable data products. The work is meaningful, the ownership is real, and the platform you help build will be a direct part of how Howard grows.</div><div> 

</div><div>Duties &amp; Responsibilities:</div><div> 

</div><div>Data Pipeline Development &amp; Integration
</div>
<div><ul><li>Build and ship production-grade data pipelines and integrations on our Azure platform, connecting the systems that run the business: financial, operational, HR, measurement, and vendor data sources.</li>
<li>Develop and maintain analytics-ready datasets for downstream consumers, gathering requirements from business stakeholders and validating that the logic reflects operational reality.</li>
<li>Build and maintain integrations across enterprise systems, treating the data platform as a central integration point that grows in value as each connection is added.</li>
<li>Participate in proof-of-concepts for new ingestion patterns, modeling approaches, or integrations that support AI and automation use cases, and help productionize the ones that work.</li></ul></div></div> 
<div>
<div>Platform Operations &amp; Reliability
</div>
<div><ul><li>Operate what you build: monitor pipelines, keep them healthy, document runbooks, and follow root causes through to resolution.
</li>
<li> Improve the platform as you go with better tests, better documentation, and better observability, so that what gets built stays built.
</li>
<li> Occasionally support analytics needs such as Power BI datasets or lightweight Python outputs when it directly accelerates a data product delivery.</li></ul></div> 
<div></div>
<div>
</div><div>Stakeholder Partnership
</div>
<div><ul><li>Partner with departments throughout the company to understand what they need and translate that into technical solutions that reflect operational reality.
</li>
<li> Explain technical concepts clearly to non-technical stakeholders, in the room and in writing.
</li>
<li> Gather requirements directly, validate logic against real business conditions, and close the loop with confidence.</li></ul> 
</div>
<div>Continuous Improvement
</div>
<div><ul><li>Identify opportunities to improve consistency, reliability, and clarity across the data platform as the business grows.
</li>
<li> Contribute to the evolution of platform practices: better patterns, better standards, better tooling, without layering in unnecessary complexity.
</li>
<li> Surface observations about how we work and bring them forward as conversations, not just problems.
</li>
<li> Help ensure the platform scales in a way that stays useful and trusted by the people who depend on it.
</li>
<li> Approach your own development the same way you approach the platform: as an ongoing practice of getting sharper, broader, and more capable over time.
</li>
<li> Engage actively in mentorship, feedback, and learning opportunities as they arise. Growth here is expected, supported, and built into how we work.</li></ul> 

 Required Skills/Abilities:
<div>
<ul><li>Genuine curiosity about the business behind the data. Asks why before how.
</li>
<li> Sound judgment and the ability to make good decisions with incomplete information.
</li>
<li> Strong communication skills, including the ability to translate technical work for non-technical audiences with patience and clarity.
</li>
<li> Comfort working on a small team where ownership is broad and collaboration is constant.
</li>
<li> Humility to learn before proposing changes, and confidence to raise real concerns when warranted.
</li>
<li> A service mindset. The goal is to make the business better, and the best technical work is the work that earns trust.
</li>
<li> Demonstrated ability to navigate ambiguity while maintaining a strong understanding of business operations and data-driven decision-making.
</li>
<li>Ability to explain technical work clearly to non-technical audiences, in the room and in writing.</li>
<li> Ability to work on-site in San Antonio, TX.</li></ul></div> 

</div></div><div><div>Education &amp; Experience
<div>
<ul><li>Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical field required; equivalent professional experience considered in lieu of degree.
</li>
<li> 3 to 6 years of professional experience in data engineering, software engineering, or a closely related technical discipline.
</li>
<li>3 to 6 years of production data engineering experience is the target range for this role, enough to ship real work confidently, with room to grow in responsibility.
</li>
<li> 3+ years building and maintaining data pipelines or integrations in a real production environment.
</li>
<li> Strong Python and SQL, comfortable writing, testing, and debugging production-grade code.
</li>
<li> Hands-on experience with the Microsoft Azure data stack: any combination of ADF, Functions, ADLS, Synapse, Databricks, or Container Apps.
</li>
<li> Comfortable with Git, CI/CD, and Azure DevOps including branching, pipelines, repos, and releases.</li></ul> 
</div>
</div><div>Preferred Experience:
</div>
<div><ul><li>Familiarity with medallion/layered architectures (Bronze/Silver/Gold) and data contracts.
</li>
<li> Experience with Power BI or other semantic-layer tooling.
</li>
<li> Exposure to midstream energy, industrial/OT systems, SCADA, historians, or measurement data.
</li>
<li>Familiarity with Airflow, data catalog tooling such as DataHub or Purview, or modern metadata management.</li>
<li>Experience operating a platform end-to-end from initial build through ongoing support.</li>
<li>Experience in energy, industrial, or operations-adjacent environments is a plus.</li></ul> 
</div>
</div><div></div><div><div>Certifications:
No formal certifications required. Relevant professional certifications are welcomed. 


Physical Demands and Hazards for Office Employees:

This position requires prolonged periods of sitting, frequent computer use, occasional lifting of office supplies, and may involve travel.

Thank you for your interest in Howard Energy Partners, an equal opportunity employer. If you need additional information, have questions, or need accommodations, please reach out to the Human Resources department at 210-298-2222. 

</div>
</div><h4 class="jobSectionHeader">Experience</h4>
Required<ul><li>
Experience working with Microsoft Azure data technologies.</li><li>
Experience developing solutions using Python and SQL.</li><li>
3 year(s): 3+ years building and maintaining data pipelines or integrations in a production environment.</li><li>
3 year(s): 3+ years of professional experience in data engineering, software engineering, or a closely related technical discipline.</li></ul><h4 class="jobSectionHeader">
Education</h4>
Required<ul><li>
Bachelors or better in Computer Science or related field</li></ul><h4 class="jobSectionHeader">
Skills</h4>
Required<ul><li>
Programming</li><li>
Software Development</li><li>
Business Intelligence</li><li>
APIs</li><li>
Database Management</li><li>
Data Analytics</li><li>
Microsoft SQL Server</li><li>
SQL</li><li>
Python</li></ul><h4 class="jobSectionHeader">
Behaviors</h4>
Required<ul><li>
Thought Provoking: Capable of making others think deeply on a subject</li><li>
Team Player: Works well as a member of a group</li><li>
Functional Expert: Considered a thought leader on a subject</li><li>
Detail Oriented: Capable of carrying out a given task with all details necessary to get the task done well</li><li>
Dedicated: Devoted to a task or purpose with loyalty or integrity</li></ul><h4 class="jobSectionHeader">
Motivations</h4>
Required<ul><li>
Growth Opportunities: Inspired to perform well by the chance to take on more responsibility</li><li>
Ability to Make an Impact: Inspired to perform well by the ability to contribute to the success of a project or the organization</li></ul>
Equal Opportunity Employer 
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.</div>

Data Engineer — Data Platform & Integrations

VIVA

<div>The client is seeking one full-time Database Engineer.
 
 
As an Azure Database Engineer, this position will participate in the analysis, design, development, implementation, and potentially ongoing support of Azure Databases and Data Lakes, with a primary focus on the Data Lakehouse and its integrated data reserves. The responsibilities will include administering, maintaining, and securing data to ensure efficient and reliable data storage solutions. The position will collaborate with cross-functional teams to optimize data workflows, support data-driven decision-making, and implement best practices for data security and integrity in Azure environments. This position also will provide mentorship to other Database Engineers.
 
 
Sample Tasks
 
Develop and implement relational and non-relational databases in Azure.
 
Develop and implement data transformations.
 
Ensure data access patterns are optimized.
 
Maintain necessary documentation.
 
Coordinate with necessary teams to meet security standards.
 
Implement disaster recovery solution.
 
Provide knowledge transfer.
 
 
Desired Qualifications
 
Experience with designing, developing, and implementing data lakes and relational and non-relational databases in Azure.
 
Experience with Databricks.
 
Experience with Oracle databases.
 
Strong experience developing and implementing data transformation solutions and cloud infrastructure integration.
 
Strong experience coding and testing programs and scripts to load data using Azure data load utilities.
 
Strong experience with CI/CD pipelines.
 
Experience with cloud computing concepts.
 
Experience with tools such as Azure Monitor, Azure Data Factory, SQL Analytics, Query Performance Insight, Azure Resource Manager, and Azure CLI/PowerShell for infrastructure management.
 
Experience in mentoring others in the needed technologies.
 
Experience developing and implementing backup and recovery strategies using tools such as Azure Backup or Geo-replication.
 
Experience with role-based access control, encryption, and network security.
 
Strong organizational and time management skills.
 
Desired 7 years&rsquo; experience designing, developing, and implementing data lakes and relational and non-relational databases in Azure.
 
Knowledge of data concepts, data modeling, schema design, and indexing strategies.
 
Knowledge of Azure SQL instances, managed instances, and elastic pools.
 
Knowledge of Data Warehouse Administration and Teradata Data Warehouse. 
 
 
VIVA is an equal opportunity employer. All qualified applicants have an equal opportunity for placement, and all employees have an equal opportunity to develop on the job. This means that VIVA will not discriminate against any employee or qualified applicant on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.</div>

Azure Database Engineer

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