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Lead Data Engineer (Databricks)

  • Job type Posted on: Jun 19, 2026
  • Experience level Rearc
  • Employment type New York, New York
  • Employment type Onsite
  • Salary Full-time

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Job Title :

Lead Data Engineer (Databricks)

Job Type :

Full-time

Job Location :

New York New York United States

Remote :

No

Jobcon Logo Job Description :

As a Lead Data Engineer at Rearc, you'll play a pivotal role in establishing and maintaining technical excellence within our data engineering team. Your deep expertise in data architecture, ETL processes, and data modeling will be instrumental in optimizing data workflows for efficiency, scalability, and reliability. You’ll work closely with cross‑functional teams to design and implement robust data solutions that align with business objectives and industry best practices. Building strong partnerships with technical teams and stakeholders will be essential as you drive data‑driven initiatives and ensure their successful delivery. What You Bring 10+ years of experience in data engineering, data architecture, or related technical fields, with a proven ability to design, build, and optimize large‑scale data ecosystems. Leading complex data engineering initiatives , architecting end‑to‑end data solutions that are scalable, reliable, and aligned with business strategy. Deep hands‑on expertise in ETL/ELT design, data warehousing, and data modeling, enabling the creation of efficient, high‑quality data pipelines and analytical foundations. Extensive experience with data integration frameworks and best practices , ensuring seamless, performant data movement across diverse systems and platforms. Advanced knowledge of cloud‑based data services and architectures , including platforms such as AWS Redshift, Azure Synapse Analytics, Google BigQuery, or equivalent technologies. Strategic and analytical thinking , allowing you to tackle complex data challenges, drive architectural decisions, and influence long‑term data strategy. Proficiency with modern data engineering frameworks, including Databricks, Spark and lakehouse technologies like Delta Lake for managing and processing large‐scale datasets. Exceptional communication and interpersonal skills , enabling effective collaboration with engineers, product teams, executives, and customers—while influencing technical direction and decision‑making. What You’ll Do As a Lead Data Engineer, you will help shape, deliver, and elevate Rearc’s data engineering practice. You’ll lead by example—combining strong technical execution with mentorship, strategic thinking, and a culture‑first approach. Engage deeply with stakeholders to understand data needs, business challenges, and technical constraints, translating them into scalable, high‑quality data solutions. Implement with a DataOps mindset , applying modern engineering practices and leveraging tools such as Apache Airflow, Databricks/Spark, Kafka, or similar technologies to build reliable, automated, and efficient data pipelines and architectures. Lead and execute complex projects , providing technical direction, setting engineering standards, and ensuring alignment with customer goals and Rearc’s principles. Mentor and develop data engineers , offering guidance, code reviews, and hands‑on support to help them grow technically and professionally. Promote knowledge sharing and thought leadership by contributing to internal and external content—writing technical blogs, sharing best practices, and fostering a culture of continuous learning and innovation. Benefits Generous time away and flexible PTO Maternity and paternity leave Access to educational resources with reimbursement for continued learning #J-18808-Ljbffr

Jobcon Logo Position Details

Posted:

Jun 19, 2026

Reference Number:

14660_B208B11BA7CDF9C6A794615E2F617ADF

Employment:

Full-time

Salary:

Not Available

City:

New York

Job Origin:

APPCAST_CPC

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As a Lead Data Engineer at Rearc, you'll play a pivotal role in establishing and maintaining technical excellence within our data engineering team. Your deep expertise in data architecture, ETL processes, and data modeling will be instrumental in optimizing data workflows for efficiency, scalability, and reliability. You’ll work closely with cross‑functional teams to design and implement robust data solutions that align with business objectives and industry best practices. Building strong partnerships with technical teams and stakeholders will be essential as you drive data‑driven initiatives and ensure their successful delivery. What You Bring 10+ years of experience in data engineering, data architecture, or related technical fields, with a proven ability to design, build, and optimize large‑scale data ecosystems. Leading complex data engineering initiatives , architecting end‑to‑end data solutions that are scalable, reliable, and aligned with business strategy. Deep hands‑on expertise in ETL/ELT design, data warehousing, and data modeling, enabling the creation of efficient, high‑quality data pipelines and analytical foundations. Extensive experience with data integration frameworks and best practices , ensuring seamless, performant data movement across diverse systems and platforms. Advanced knowledge of cloud‑based data services and architectures , including platforms such as AWS Redshift, Azure Synapse Analytics, Google BigQuery, or equivalent technologies. Strategic and analytical thinking , allowing you to tackle complex data challenges, drive architectural decisions, and influence long‑term data strategy. Proficiency with modern data engineering frameworks, including Databricks, Spark and lakehouse technologies like Delta Lake for managing and processing large‐scale datasets. Exceptional communication and interpersonal skills , enabling effective collaboration with engineers, product teams, executives, and customers—while influencing technical direction and decision‑making. What You’ll Do As a Lead Data Engineer, you will help shape, deliver, and elevate Rearc’s data engineering practice. You’ll lead by example—combining strong technical execution with mentorship, strategic thinking, and a culture‑first approach. Engage deeply with stakeholders to understand data needs, business challenges, and technical constraints, translating them into scalable, high‑quality data solutions. Implement with a DataOps mindset , applying modern engineering practices and leveraging tools such as Apache Airflow, Databricks/Spark, Kafka, or similar technologies to build reliable, automated, and efficient data pipelines and architectures. Lead and execute complex projects , providing technical direction, setting engineering standards, and ensuring alignment with customer goals and Rearc’s principles. Mentor and develop data engineers , offering guidance, code reviews, and hands‑on support to help them grow technically and professionally. Promote knowledge sharing and thought leadership by contributing to internal and external content—writing technical blogs, sharing best practices, and fostering a culture of continuous learning and innovation. Benefits Generous time away and flexible PTO Maternity and paternity leave Access to educational resources with reimbursement for continued learning #J-18808-Ljbffr

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