6 data pipeline engineer jobs at 5 companies in Winnsboro, SC
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AVP, Data Services – Lead Data Engineer
Fort Mill or Charlotte or Austin
$119k-$198k/yrOnsiteFull Time
LPL FinancialNASDAQ: LPLA: Provides wealth management and brokerage services to financial advisors.
7+ YOE2+ Mgmt7+ years data engineering experience, 2+ years technical/people lead experience, bachelor\u0002s in a technical field, hands-on with cloud-native data pipelines, reference data, APIs, and data governance.
7+ YOE2+ Mgmt7+ years data engineering experience, 2+ years technical lead/people leadership, cloud-native data pipeline and API development, experience with reference/master data and data governance, Bachelor's degree required.
Atlanta or Chicago or Columbia or New York City or Charlotte
$100k-$130k/yrHybridFull Time
CapgeminiEuronext Paris: CAP: Provides global IT consulting and digital transformation services.
5+ YOE5–7 years in data engineering/marketing technology, 2+ years with LiveRamp/Habu clean room, strong SQL, Python/Spark, cloud pipeline experience, and familiarity with privacy-safe aggregation and identity resolution.
LiveRamp Clean Room (Habu), InfoSum, AWS Clean Rooms, Google Ads Data Hub, SQL, Python, Spark, GCP, AWS, Azure
Integer Technologies: Applied research and product development for national security.
4+ YOEUS citizen able to obtain DoD/DoW Secret clearance,4+ years cloud architecture experience,knowledge of cloud-native data pipelines,Kubernetes,security/compliance (FedRAMP,NIST800-53),and strong communication;up to 20% travel.
LTIMindtreeNational Stock Exchange of India: LTIM: Global technology consulting and digital solutions.
6+ YOERequires 6–8 years of experience developing and supporting Microsoft Fabric data solutions, including data pipelines, notebooks, PySpark, and data modeling, plus Power BI and DAX experience.
Microsoft Fabric, Microsoft OneLake, PySpark, Power BI, DAX, Gateway
Selective InsuranceNASDAQ: SIGI: Provider of commercial and personal property and casualty insurance.
8+ YOE8+ years in data engineering/analytics/platform engineering; strong leadership; cloud data platforms; Databricks or lakehouse; Data pipelines; CI/CD; data modeling; PySpark and SQL; strong communication.