Data Engineer

King & Sykes; United States; Hybrid; USD 115,000 - 140,000; Full time

Job summary

A leading energy company is seeking a Data Engineer to design and manage the data infrastructure for their analytics and operations. This role requires expertise in data modeling, database management, and cloud services like Azure. Candidates should have a Bachelor’s degree and 3-5 years of experience in data engineering. The position offers a competitive salary and is open to remote work.

Benefits

Medical insurance

401(k)

Qualifications

• Experience designing normalized and denormalized data models for operations and analytics.
• Proficiency in managing relational and analytical databases.
• Strong SQL and experience with ETL/ELT tools.
• Python skills for data manipulation and scripting.

Responsibilities

• Help shape and operate the data infrastructure.
• Work with developers, analysts, and AI engineers to design robust systems.
• Build and maintain a medallion architecture data warehouse.
• Develop and maintain ELT/ETL pipelines for data ingestion.

Skills

Experience designing normalized and denormalized data models for operations and analytics

Proficiency in managing relational and analytical databases such as SQL Server, PostgreSQL, and Azure Synapse

Strong SQL and experience with ETL/ELT tools

Python skills for data manipulation and scripting

Familiarity with Parquet, JSON, flat files

Solid understanding of Azure data services

Experience with web data scraping tools

Bachelor’s degree in Computer Science, Data Engineering, or a related discipline

3–5 years of experience in data engineering or a related field

Education

Bachelor’s degree in Computer Science, Data Engineering, or a related discipline

Tools

SQL Server

PostgreSQL

Azure Synapse

Azure Data Factory

Job description

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This range is provided by King & Sykes. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$115,000.00/yr - $140,000.00/yr

A dynamic and growing team is seeking a Data Engineer to help build next-generation technology solutions as part of a broader digital transformation. This is a greenfield opportunity to design, build, and own the data infrastructure that underpins analytics, operations, and internal applications for a private equity backed energy company.

You’ll join a lean, high-impact team where data is a strategic focus. The role involves defining data flows across the organization, implementing modern architecture patterns, and ensuring access to reliable, well-modeled, and timely information for both technical and business users.

Responsibilities

As a Data Engineer, you will help shape and operate the data infrastructure supporting decision-making, analytics, and automation. You’ll work with developers, analysts, and AI engineers to design robust systems and build an enterprise data warehouse from scratch. Responsibilities include:

• Translating business requirements into logical and physical data models optimized for transactional and analytical use.
• Designing and optimizing databases, including tables, indexes, and views for use in internal applications and BI tools.
• Building and maintaining a medallion architecture (bronze, silver, gold) data warehouse to ensure quality data ingestion and transformation.
• Collaborating with AI engineers to provide structured data for AI/ML workflows and integrating vector databases for semantic capabilities.
• Developing and maintaining ELT/ETL pipelines for data ingestion from APIs, flat files, web scraping, and internal systems.
• Enabling analytics by creating consumable datasets, materialized views, and well-documented schemas for use in tools like Power BI and Excel.
• Ensuring performance and reliability of data infrastructure and resolving issues across data workflows.
• Designing and managing cloud-native platforms using Azure services such as Data Factory, Synapse Analytics, Azure SQL, and Blob Storage.
• Implementing Infrastructure as Code (IaC) using ARM, Bicep, or Terraform for provisioning and securing Azure-based data infrastructure.
• Administering operational data systems, including alerting, monitoring, backups, and recovery.
• Collaborating across teams (development, analytics, GIS, product) to ensure data availability and integration.
• Documenting systems and mentoring teammates on tools, practices, and design patterns.

Qualifications

• Experience designing normalized and denormalized data models for operations and analytics.
• Proficiency in managing relational and analytical databases such as SQL Server, PostgreSQL, and Azure Synapse.
• Strong SQL and experience with ETL/ELT tools like Azure Data Factory, Synapse Pipelines, and Airflow (Python).
• Python skills for data manipulation and scripting using libraries like pandas or PySpark.
• Familiarity with Parquet, JSON, flat files, and both structured and unstructured data sources.
• Solid understanding of Azure data services (ingestion, storage, compute, orchestration).
• Experience with web data scraping tools such as Playwright, Puppeteer, BeautifulSoup, or Selenium.
• Bachelor’s degree in Computer Science, Data Engineering, or a related discipline.
• 3–5 years of experience in data engineering or a related field.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Industries

  Oil and Gas and Data Infrastructure and Analytics

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Inferred from the description for this job

Medical insurance

401(k)

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