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Sr. Data Engineer

McLane Global is seeking a Sr. Data Engineer to join our dynamic team. In this role, you will play a crucial part in shaping our data strategy and elevating our data infrastructure to new heights. As a leading provider in our industry, we recognize that data is at the heart of our operations and decisions, and we need a skilled engineer to help us harness its full potential. You will work closely with cross-functional teams to design, develop, and maintain robust data pipelines and architectures, enabling the organization to derive actionable insights and drive innovative solutions. We are looking for a candidate who is passionate about data engineering and has a proven track record of building scalable and efficient data systems. The ideal candidate will possess deep technical knowledge of data engineering practices, be adept at utilizing various ETL tools, and have hands-on experience with cloud platforms. If you thrive in a fast-paced environment and are excited about leveraging data to fuel business growth, we want to hear from you. Join us at McLane Global, where you'll have the opportunity to work with cutting-edge technologies and contribute to exciting projects that make a real difference in our industry.

Responsibilities

•       Design, build, and optimize scalable data pipelines, warehouses, and processing systems using Azure Synapse, Databricks, Spark Pools, and Microsoft Fabric to ensure efficient data flow and accessibility. 

•       Develop and manage data integrations across multiple platforms, including D365, Dual Write, Azure Data Studio, and Power Platform, ensuring seamless data exchange between enterprise systems. 

•       Implement and optimize EDI integrations, API-based data exchanges, and event-driven architectures to facilitate real-time and batch data processing. 

•       Leverage Azure Data Services, including Azure Data Factory, Azure Data Lake, and Azure Storage, to implement cloud-based data solutions that optimize performance, cost, and scalability. 

•       Design and maintain reports and dashboards using Power BI and SSRS, integrating complex data models to provide actionable insights for business decision-making. 

•       Implement data governance, security, and compliance policies, ensuring adherence to industry standards and regulations such as GDPR, HIPAA, and SOC2

•       Develop and maintain ETL/ELT processes using Azure Data Factory, Synapse Pipelines, and Databricks, ensuring efficient data transformation and movement across systems. 

•       Manage real-time and batch data processing with Apache Spark, Azure Stream Analytics, and Event Hubs to support high-volume data workflows. 

•       Build and optimize Data Lakehouse Architectures, ensuring structured and unstructured data can be effectively processed and analyzed. 

•       Perform database performance tuning, query optimization, and indexing strategies in Azure SQL, Synapse, and Cosmos DB for high-performance data access. 

•       Develop and manage CI/CD pipelines for data workflows using Azure DevOps and Git, ensuring automated deployment and version control of data assets. 

•       Work with Data Scientists and Analysts to enable machine learning and advanced analytics capabilities by structuring data for AI/ML models. 

•       Troubleshoot and resolve complex data pipeline failures, latency issues, and data integrity problems across distributed cloud environments. 

•       Implement monitoring and alerting mechanisms using Azure Monitor, Log Analytics, and Application Insights to proactively detect and resolve performance bottlenecks. 

•       Collaborate with business leaders, department heads, and cross-functional teams to define data strategies and deliver scalable, high-performance analytics solutions.

•       Strong hands-on experience with Microsoft Azure Data Services, including Azure Synapse, Databricks, Data Factory, Data Lake, and Azure SQL.

•       Extensive experience in ETL/ELT development, data integration, and data transformation using Azure Data Factory, Synapse Pipelines, and Databricks.

•       Proficiency in Apache Spark, Spark Pools, and Azure Stream Analytics for real-time and batch data processing.

•       Strong coding skills in Python, SQL, or PowerShell for data processing and automation.

•       Expertise in Azure SQL, Synapse Analytics, Cosmos DB, and NoSQL databases, including query optimization and performance tuning.

•       Experience in API-based data integrations, EDI (Electronic Data Interchange), and working with REST/SOAP APIs for seamless system communication.

•       Knowledge of data privacy, governance, and security best practices, including compliance with GDPR, HIPAA, and SOC2.

•       Experience with Power BI, SSRS, and other BI tools for designing interactive reports and dashboards.

•       Hands-on experience with CI/CD pipelines using Azure DevOps, Git, and Terraform for automating deployments and version control.

•       Familiarity with Azure Monitor, Log Analytics, and Application Insights to track system health and optimize data workflows.

•       Strong analytical and debugging skills to identify, diagnose, and resolve data pipeline failures in distributed cloud environments.

•       Ability to work cross-functionally with business leaders, data scientists, and developers, translating business requirements into scalable data solutions.

•       Azure certifications such as Microsoft Certified: Azure Data Engineer Associate (DP-203) or equivalent are preferred.

•       Proficient knowledge of Lean tools and methodologies (e.g., 5S, PDCA, Process Mapping, Value Stream Mapping, Kaizen, Root Cause Analysis).

•       Strong analytical and problem-solving abilities, with a data-driven approach to decision-making.

•       Exceptional interpersonal and communication skills, with the ability to influence and engage employees at all organizational levels. • Proficiency in data analysis software and Microsoft Excel, PowerPoint, Word, and Visio. 

•       Competitive base compensation  

•       Full Benefits including Medical, Dental and Vision effective on the first day of employment 

•       401(k) with Employer Match (quarterly enrollment)

•       Paid Holidays (no waiting period to receive holiday pay)

•       Paid vacation, personal, and sick days effective on first day of employment

•       All offers are contingent upon passing a background check and drug screening  

•       No company visa sponsorships    

•       No phone call or walk in inquiries for this position, apply online to be considered  

Average salary estimate

$140000 / YEARLY (est.)
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$120000K
$160000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Sr. Data Engineer, Mclane Global

McLane Global is excited to welcome a Sr. Data Engineer to our innovative team! In this pivotal position, you will have the opportunity to transform our data landscape and influence our comprehensive data strategy. Data drives our operations and decision-making, and as such, we are in search of a talented engineer who can help us optimize its potential. Working collaboratively with dynamic cross-functional teams, you'll design, develop, and maintain robust data pipelines and architectures that empower our organization to extract actionable insights and spearhead innovative solutions. Your passion for data engineering will be evident as you utilize your extensive experience with ETL tools and cloud platforms. In the high-energy environment at McLane Global, you will be hands-on with cutting-edge technologies while contributing to exciting projects that truly make a difference. If you are eager to advance your skills in a role that champions data and promotes business growth, we encourage you to apply and embark on this thrilling journey with us!

Frequently Asked Questions (FAQs) for Sr. Data Engineer Role at Mclane Global
What are the main responsibilities of a Sr. Data Engineer at McLane Global?

At McLane Global, the Sr. Data Engineer is tasked with designing, building, and optimizing scalable data pipelines and architectures. This role involves managing data integrations across various platforms, developing ETL processes, and ensuring real-time data processing. You'll work with Azure Data Services, implement data governance policies, design insightful reports using Power BI, and collaborate with cross-functional teams to define and deliver data strategies.

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What qualifications are required to become a Sr. Data Engineer at McLane Global?

To qualify for the Sr. Data Engineer position at McLane Global, candidates should have strong experience in data engineering practices. This includes proficiency in Azure Data Services, extensive ETL/ELT development skills, and expertise in Apache Spark. A solid understanding of data privacy regulations such as GDPR and HIPAA is also important. Ideal candidates will have an Azure certification, strong coding skills, and the ability to work collaboratively in fast-paced settings.

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What technologies will a Sr. Data Engineer at McLane Global be working with?

In the role of Sr. Data Engineer at McLane Global, you will be working with various cutting-edge technologies, including Azure Synapse, Databricks, Power BI, and more. Additionally, your expertise will extend to tools such as Azure Data Factory, Azure Data Lake, and Azure Stream Analytics to optimize performance and scalability in cloud-based solutions.

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What skills are important for success as a Sr. Data Engineer at McLane Global?

Success as a Sr. Data Engineer at McLane Global hinges on strong analytical skills for identifying data pipeline issues, solid programming knowledge in Python or SQL, and an understanding of data governance best practices. Proficiency in using CI/CD pipelines, coupled with stellar communication skills to foster collaboration among teams, is also key to thriving in this role.

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What benefits can a Sr. Data Engineer expect at McLane Global?

At McLane Global, the benefits package for a Sr. Data Engineer includes competitive base compensation, comprehensive health insurance (medical, dental, and vision) effective from day one, and a 401(k) plan with employer match. Further, you will enjoy paid holidays, vacation time, personal days, and sick leave from your first day.,

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Common Interview Questions for Sr. Data Engineer
Can you describe your experience with cloud data solutions as a Sr. Data Engineer?

When answering this question, highlight specific cloud platforms you've worked with, such as Azure, and discuss the various data services you've used. Mention any projects where you implemented cloud-based solutions and the outcomes for the organization, demonstrating your hands-on experience with tools like Azure Data Factory or Databricks.

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How do you approach designing scalable data pipelines?

Discuss your systematic approach to designing scalable data pipelines, including steps such as identifying data requirements, selecting the right technologies, and optimizing for performance. Emphasize the importance of integrating monitoring and alerting mechanisms to ensure these pipelines run efficiently.

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What are your strategies for optimizing data transformation processes?

Provide insights into your methods for optimizing ETL/ELT processes, such as using parallel processing, employing data partitioning techniques, or leveraging cloud capabilities. Explain any specific tools you use and how they aid in improving transformation speed and resource usage.

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Describe a challenging data integration project you worked on.

Here, share a specific situation involving complex data integration, outlining the challenges you faced, your approach to solving those issues, and the final results. This shows your problem-solving skills and adaptability in real-world scenarios.

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How do you ensure data quality in your pipelines?

Talk about the practices you implement to validate data accuracy and consistency, such as automated testing, data profiling, or checksums. Emphasize the importance of data governance and the tools you use to maintain high data quality standards.

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What tools do you prefer for monitoring data pipelines?

Mention your preferred tools for monitoring pipelines, explaining how these tools help you identify bottlenecks or failures. Discuss your experience with tools like Azure Monitor or custom solutions and how they impact data flow efficiency.

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How do you handle data security and compliance?

Explain your understanding of data security protocols, including GDPR and HIPAA compliance. Discuss the measures you take to ensure data is protected at various stages from ingestion to processing and storage, highlighting specific tools or practices.

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What is your experience with data lakes and data warehouse architecture?

Share any projects where you've designed or migrated data to a lake or warehouse. Discuss the differences between the architectures and the criteria for choosing one over another based on business needs or data types.

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How do you stay updated with the latest trends in data engineering?

Share strategies you use to stay educated about new technologies, attending webinars, following relevant blogs, or being active in online communities. Emphasize your commitment to continuous learning in the fast-evolving field of data engineering.

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What are your best practices for collaborating with data scientists and analysts?

Discuss how you create clear communication channels, involve them early in the data pipeline design, and maintain transparency throughout the development process. Explain how this collaboration enhances overall data utilization and analysis.

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McLane Global’s vast international network and domestic buying power has permitted us to become one of the premier exporters of American Brands. We are one of the largest exporters of American branded foods Including Lady Liberty Foods. This, co...

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Full-time, remote
DATE POSTED
April 10, 2025

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