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Blend360
Lead Data Engineer
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Based on Maryland data
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What they do
A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.
$112,698 / year median in Maryland
+11% projected growth
Job Description
Company Description
Job DescriptionWe are seeking a Lead Data Engineer to support a large-scale healthcare data platform initiative focused on modernizing data ingestion, automation, and semantic layer capabilities within Google Cloud Platform (GCP). This role will play a critical part in building scalable, reliable, and business-ready data solutions that enable enterprise analytics and reporting across the organization. The ideal candidate brings strong hands-on engineering expertise, deep knowledge of cloud-native data platforms, and experience leading technical implementation efforts in complex enterprise healthcare environments. What You'll Do Design, build, and optimize scalable data pipelines supporting enterprise healthcare analytics and reporting use cases Lead automation efforts across ingestion, transformation, orchestration, and operational monitoring workflows Develop and maintain ingestion frameworks for structured and semi-structured healthcare data sources Build and expand semantic data layers within GCP and BigQuery to support consistent, trusted business reporting and analytics consumption Design scalable ELT/ETL workflows leveraging modern cloud-native architecture patterns Partner closely with architects, analytics teams, and business stakeholders to translate data requirements into scalable technical solutions Optimize BigQuery performance, partitioning, and cost management strategies Implement engineering best practices for testing, observability, reliability, and deployment automation Support data governance, data quality, and metadata management initiatives across the platform Mentor junior engineers and provide technical leadership across delivery teams QualificationsRequired Skills Strong expertise in Google Cloud Platform (GCP), particularly: BigQueryCloud StorageCloud Composer / orchestration toolingDataflow or modern ingestion frameworks Experience designing and building scalable data ingestion and pipeline automation frameworks Strong understanding of semantic layer development and dimensional modeling concepts Advanced SQL and Python development skills Experience with ETL/ELT pipeline design and orchestration Familiarity with CI/CD, infrastructure automation, and cloud engineering best practices Strong understanding of data quality, observability, and operational reliability principles Experieng with AI driven workflows, and orchestration design patterns. Preferred Experience Experience working with healthcare data ecosystems and regulated enterprise environments Familiarity with healthcare data standards or payer/provider analytics platforms Experience supporting enterprise BI and analytics initiatives Exposure to dbt, Looker, or semantic modeling frameworks is a plus Required Experience 7+ years of experience in data engineering or cloud data platform development Proven experience delivering enterprise-scale cloud data solutions in GCP environments Experience leading technical workstreams or mentoring engineering teams Consulting or client-facing experience strongly preferred What Makes You Successful You are passionate about building scalable and maintainable cloud-native data solutions You balance hands-on engineering execution with technical leadership and collaboration You communicate effectively with both technical and business stakeholders You thrive in fast-paced, delivery-focused environments You bring strong ownership, curiosity, and continuous improvement mindset to your work Additional InformationThe starting pay range for this role is $125,000 - $160,000. Actual compensation within the range will be dependent on several factors including but not limited to relevant experience, skills, certifications, training, and location. It is not typical for an individual to be hired at or near the top of the range and determining factors for compensation are considered for each individual circumstance.
BLEND360
is an acclaimed, forward-thinking Data, Digital Marketing, & AI Solutions Company, dedicated to fueling remarkable outcomes for our Fortune 500 clients. Our trajectory is one of continuous expansion, emerging at the crossroads of cutting-edge analytics, data proficiency, technology, and digital marketing excellence.Job DescriptionWe are seeking a Lead Data Engineer to support a large-scale healthcare data platform initiative focused on modernizing data ingestion, automation, and semantic layer capabilities within Google Cloud Platform (GCP). This role will play a critical part in building scalable, reliable, and business-ready data solutions that enable enterprise analytics and reporting across the organization. The ideal candidate brings strong hands-on engineering expertise, deep knowledge of cloud-native data platforms, and experience leading technical implementation efforts in complex enterprise healthcare environments. What You'll Do Design, build, and optimize scalable data pipelines supporting enterprise healthcare analytics and reporting use cases Lead automation efforts across ingestion, transformation, orchestration, and operational monitoring workflows Develop and maintain ingestion frameworks for structured and semi-structured healthcare data sources Build and expand semantic data layers within GCP and BigQuery to support consistent, trusted business reporting and analytics consumption Design scalable ELT/ETL workflows leveraging modern cloud-native architecture patterns Partner closely with architects, analytics teams, and business stakeholders to translate data requirements into scalable technical solutions Optimize BigQuery performance, partitioning, and cost management strategies Implement engineering best practices for testing, observability, reliability, and deployment automation Support data governance, data quality, and metadata management initiatives across the platform Mentor junior engineers and provide technical leadership across delivery teams QualificationsRequired Skills Strong expertise in Google Cloud Platform (GCP), particularly: BigQueryCloud StorageCloud Composer / orchestration toolingDataflow or modern ingestion frameworks Experience designing and building scalable data ingestion and pipeline automation frameworks Strong understanding of semantic layer development and dimensional modeling concepts Advanced SQL and Python development skills Experience with ETL/ELT pipeline design and orchestration Familiarity with CI/CD, infrastructure automation, and cloud engineering best practices Strong understanding of data quality, observability, and operational reliability principles Experieng with AI driven workflows, and orchestration design patterns. Preferred Experience Experience working with healthcare data ecosystems and regulated enterprise environments Familiarity with healthcare data standards or payer/provider analytics platforms Experience supporting enterprise BI and analytics initiatives Exposure to dbt, Looker, or semantic modeling frameworks is a plus Required Experience 7+ years of experience in data engineering or cloud data platform development Proven experience delivering enterprise-scale cloud data solutions in GCP environments Experience leading technical workstreams or mentoring engineering teams Consulting or client-facing experience strongly preferred What Makes You Successful You are passionate about building scalable and maintainable cloud-native data solutions You balance hands-on engineering execution with technical leadership and collaboration You communicate effectively with both technical and business stakeholders You thrive in fast-paced, delivery-focused environments You bring strong ownership, curiosity, and continuous improvement mindset to your work Additional InformationThe starting pay range for this role is $125,000 - $160,000. Actual compensation within the range will be dependent on several factors including but not limited to relevant experience, skills, certifications, training, and location. It is not typical for an individual to be hired at or near the top of the range and determining factors for compensation are considered for each individual circumstance.