{"id":3900463,"url":"https://alion.io/job/mclane-company-sr-data-engineering-manager","title":"Sr Data Engineering Manager","company":{"id":1904902,"name":"McLane Company","domain":"mclaneco.com","url":"https://alion.io/company/mclaneco","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":79,"open_postings":84,"ghost_share":0,"stale_share":0.821,"repost_share":0.024,"time_to_fill_p50_days":32,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Round Rock, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FinOps","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"pySpark","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Azure Data Factory","optional":true},{"name":"Data Vault","optional":true},{"name":"Git","optional":true},{"name":"IAM","optional":true},{"name":"Incident Management","optional":true},{"name":"Python","optional":true},{"name":"Rest API","optional":true}],"status":"live","first_seen_at":"2026-11-07T00:34:50Z","employer_posted_date":"2026-11-07","last_verified_at":"2026-11-07T20:31:02Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Take your career further with McLane!\nMcLane teammates, the driving force behind our success, are diverse professionals who work together seamlessly to keep our operations running smoothly. As a teammate, you will pair your dedication, expertise, and collaborative spirit with your fellow teammates to serve America’s most beloved brands. McLane leaders think long-term, act with purpose, and inspire high performance. They lead with accountability, communicate clearly, and drive results through collaboration, innovation, and continuous growth. They empower each teammate to learn from industry leaders, develop their skills, and build lasting connections nationwide.\nWe’re looking for an enthusiastic and experienced Sr. Data Engineering Manager who is passionate about applying AI while building and evolving modern data engineering pipelines. This leader will combine strong technical expertise with seasoned people leadership and the ability to understand stakeholder requirements, communicate effectively across technical and business teams, and translate business needs into scalable data solutions. The role will help build an AI-ready data ecosystem that supports analytics, automation, and digital supply chain outcomes.\nThis is a hybrid position which will require the candidate to report and work from the office at least three days a week. Therefore, interested candidates should be within a 50-minute radius from Temple, TX.\nBenefits you can count on:\nDay 1 Benefits: medical, dental, and vision insurance, FSA/HSA, and company-paid life insurance\nPaid time off begins day one.\n401(k) Profit Sharing Plan after 90 days.\nAdditional benefits: pet insurance, maternity/paternity leave, employee assistance programs, discount programs, tuition reimbursement program, and more!\nWhat You'll Do:\nDefine and execute the data engineering strategy and operating model. (domain teams, platform teams, governance) \nLead the design, development, and modernization of scalable data engineering pipelines.\nChampion the application of AI across data engineering practices, platforms, and products.\nLead cloud and hybrid platform modernization. (lakehouse, streaming, real-time + batch ingestion, legacy migration) \nEstablish enterprise standards & architectures. (ELT/ETL, medallion, semantic layer, data modeling, streaming) \nDrive data governance. (quality, lineage, security, access, SLAs, data contracts) \nEnsure compliance & audit readiness. (privacy-by-design, SOX, GDPR/CCPA alignment) \nDeliver scalable, reliable, cost-optimized platforms. (performance engineering, FinOps) \nBuild reusable data pipelines & domain data products enabling analytics and AI/ML. \nPartner with stakeholders and business leaders to understand requirements, translate business needs into technical solutions, and communicate priorities, tradeoffs, and outcomes effectively.\nImplement DataOps practices. (CI/CD, testing, observability, incident response) \nLead and develop high-performing teams. (hiring, coaching, succession planning) \nManage vendor strategy, tooling, and technology selection. \nDrive continuous improvement through SLIs/SLOs, pipeline performance, data quality, and cost metrics.\nWhat We're Looking For:\nEducation: Bachelor’s degree in Computer Science, Engineering, Statistics, or related field.\nExperience 7+ years in data engineering / data platform engineering, including 3+ years leading teams. (manager-of-managers preferred) \nSeasoned leader with demonstrated success managing technical teams, priorities, and stakeholder expectations. \nStrong enthusiasm for AI and demonstrated interest in applying AI to data engineering, automation, analytics, and business solutions.\nStrong stakeholder management and communication skills with the ability to translate technical concepts and requirements for both technical and non-technical audiences. \nData Engineering in GCP is preferred. \nCloud Composer (Airflow), Dataproc (Spark/PySpark), Dataflow, Dataform, BigQuery SQL transformations \nDatastream (CDC), Cloud Storage (GCS), Pub/Sub, Knowledge Catalog, Data Quality frameworks, Metadata & lineage \nMicrosoft Fabric experience is a plus (Skillset listed below): Fabric Lakehouse, Fabric Notebooks (PySpark), Data Factory Pipelines, Dataflow Gen2, Spark SQL, Git / source control, REST APIs and JSON processing, Delta/Parquet file formats \n\nStrong expertise in Spark, batch + streaming pipelines, and modern data architectures. \nAdvanced proficiency in SQL & Python. \nProven experience with ELT/ETL, orchestration, data modeling (dimensional/Data Vault), and metadata/lineage. \nExpertise in DataOps & engineering excellence. (CI/CD, IaC, Git, monitoring, incident management) \nSolid understanding of data governance, security, and privacy controls. (IAM, encryption, retention, lineage) \nExperience translating business needs into technical solutions and driving cross-functional alignment. \nBackground in vendor evaluation, budgeting, and tool selection. \nStrong communication skills with ability to influence at all levels. \nWorking knowledge of AI/ML, data science, or advanced analytics concepts.\nAbility to lead multiple priorities and large-scale initiatives simultaneously.\nThis position requires the ability to read, write, and understand English at a level sufficient to perform job-related tasks effectively and safely. This includes understanding work instructions, safety protocols, and communications essential to the role. The requirement is directly related to the nature of the job and ensures compliance with workplace safety and operational standards.\nFit the following? We want you here!\nTeamwork oriented\nOrganized\nProblem solver\nDetailed\nOur roadmap. Our story.\nWe’ve been forging our path as a leader in the distribution industry since 1894. Building an expansive nationwide network of team members for 130+ years has allowed us to stay agile for our clients across the restaurant, retail, and e-commerce industries. We look to the future and are ready to continue making industry-defining moves by embracing the newest technology into our practices, continuing team member training, and emphasizing our people-centered culture.\nCandidates may be subject to a background check and drug screen, in accordance with applicable laws.\nAll applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.\nFor our complete EEO and Pay Transparency statement, please visit https://www.mclaneco.com/legal/employment/\nTake your career further with McLane!\nMcLane teammates, the driving force behind our success, are diverse professionals who work together seamlessly to keep our operations running smoothly. As a teammate, you will pair your dedication, expertise, and collaborative spirit with your fellow teammates to serve America’s most beloved brands. McLane leaders think long-term, act with purpose, and inspire high performance. They lead with accountability, communicate clearly, and drive results through collaboration, innovation, and continuous growth. They empower each teammate to learn from industry leaders, develop their skills, and build lasting connections nationwide.\nWe’re looking for an enthusiastic and experienced Sr. Data Engineering Manager who is passionate about applying AI while building and evolving modern data engineering pipelines. This leader will combine strong technical expertise with seasoned people leadership and the ability to understand stakeholder requirements, communicate effectively across technical and business teams, and translate business needs into scalable data solutions. The role will help build an AI-ready data ecosystem that supports analytics, automation, and digital supply chain outcomes.\nThis is a hybrid position which will require the candidate to report and work from the office at least three days a week. Therefore, interested candidates should be within a 50-minute radius from Temple, TX.\nBenefits you can count on:\nDay 1 Benefits: medical, dental, and vision insurance, FSA/HSA, and company-paid life insurance\nPaid time off begins day one.\n401(k) Profit Sharing Plan after 90 days.\nAdditional benefits: pet insurance, maternity/paternity leave, employee assistance programs, discount programs, tuition reimbursement program, and more!\nWhat You'll Do:\nDefine and execute the data engineering strategy and operating model. (domain teams, platform teams, governance) \nLead the design, development, and modernization of scalable data engineering pipelines.\nChampion the application of AI across data engineering practices, platforms, and products.\nLead cloud and hybrid platform modernization. (lakehouse, streaming, real-time + batch ingestion, legacy migration) \nEstablish enterprise standards & architectures. (ELT/ETL, medallion, semantic layer, data modeling, streaming) \nDrive data governance. (quality, lineage, security, access, SLAs, data contracts) \nEnsure compliance & audit readiness. (privacy-by-design, SOX, GDPR/CCPA alignment) \nDeliver scalable, reliable, cost-optimized platforms. (performance engineering, FinOps) \nBuild reusable data pipelines & domain data products enabling analytics and AI/ML. \nPartner with stakeholders and business leaders to understand requirements, translate business needs into technical solutions, and communicate priorities, tradeoffs, and outcomes effectively.\nImplement DataOps practices. (CI/CD, testing, observability, incident response) \nLead and develop high-performing teams. (hiring, coaching, succession planning) \nManage vendor strategy, tooling, and technology selection. \nDrive continuous improvement through SLIs/SLOs, pipeline performance, data quality, and cost metrics.\nWhat We're Looking For:\nEducation: Bachelor’s degree in Computer Science, Engineering, Statistics, or related field.\nExperience 7+ years in data engineering / data platform engineering, including 3+ years leading teams. (manager-of-managers preferred) \nSeasoned leader with demonstrated success managing technical teams, priorities, and stakeholder expectations. \nStrong enthusiasm for AI and demonstrated interest in applying AI to data engineering, automation, analytics, and business solutions.\nStrong stakeholder management and communication skills with the ability to translate technical concepts and requirements for both technical and non-technical audiences. \nData Engineering in GCP is preferred. \nCloud Composer (Airflow), Dataproc (Spark/PySpark), Dataflow, Dataform, BigQuery SQL transformations \nDatastream (CDC), Cloud Storage (GCS), Pub/Sub, Knowledge Catalog, Data Quality frameworks, Metadata & lineage \nMicrosoft Fabric experience is a plus (Skillset listed below): Fabric Lakehouse, Fabric Notebooks (PySpark), Data Factory Pipelines, Dataflow Gen2, Spark SQL, Git / source control, REST APIs and JSON processing, Delta/Parquet file formats \n\nStrong expertise in Spark, batch + streaming pipelines, and modern data architectures. \nAdvanced proficiency in SQL & Python. \nProven experience with ELT/ETL, orchestration, data modeling (dimensional/Data Vault), and metadata/lineage. \nExpertise in DataOps & engineering excellence. (CI/CD, IaC, Git, monitoring, incident management) \nSolid understanding of data governance, security, and privacy controls. (IAM, encryption, retention, lineage) \nExperience translating business needs into technical solutions and driving cross-functional alignment. \nBackground in vendor evaluation, budgeting, and tool selection. \nStrong communication skills with ability to influence at all levels. \nWorking knowledge of AI/ML, data science, or advanced analytics concepts.\nAbility to lead multiple priorities and large-scale initiatives simultaneously.\nThis position requires the ability to read, write, and understand English at a level sufficient to perform job-related tasks effectively and safely. 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