Role at a glance
- Salary
- $219.1K – $301.3K/yr
- Location
- United States Remote - US - Massachusetts
- Work arrangement
- On-site
- Employment
- Full-time
- Education
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
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Role Summary
The Sr. Specialist Solutions Architect – Data Engineering & Warehousing guides strategic enterprise customers through cloud data engineering transformations and supports Solutions Architects in technical evaluations and analytics workload optimization. The role serves as a data engineering and lakehouse architecture domain expert aligned with the Databricks Data Intelligence Platform.
What You'll Do
- Provide technical leadership for building, scaling, and optimizing big data and large-scale data warehousing workloads.
- Architect production-ready pipelines and conduct end-to-end performance testing, load testing, and optimization.
- Build expertise in data lake architecture, high-velocity streaming, automated ingestion workflows, and data observability.
- Partner with Solutions Architects on pre-sales engagements, including proofs of concept, workload sizing estimations, and custom...
- Lead workshops, hackathons, and conference presentations to enable adoption and contribute to the Databricks community.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Requires deep expertise in data and software engineering, data applications, data warehousing and migration, data observability and security, modern lakehouse architectures, and production-level SQL plus Python, Scala, or Java experience.
Required
- 8+ years of experience in a technical role
- Streaming technologies such as Spark Streaming or Kafka
- Batch ingestion, performance tuning, and troubleshooting complex Spark workloads
- Building or supporting data-driven use cases, predictive analytics pipelines, or customer analytics platforms
- Migrating EDW workloads across OLAP/OLTP systems
- Advanced query tuning, governance, and MPP debugging
- Telemetry, high-velocity log ingestion, anomaly detection, and familiarity with SIEM tools such as Splunk, Elastic, or Sentinel
- Modern lakehouse architectures, including Delta Lake, data modeling, and BI integration, across AWS, Azure, or GCP
Preferred
- Databricks certifications
Original job description
Content provided by the employer
Original job description
Content provided by the employer
FEQ327R204
As a Sr. Specialist Solutions Architect (SSA) – Data Engineering & Warehousing, you will guide strategic enterprise customers through cloud data engineering transformations across a wide variety of mission-critical use cases.
In this customer-facing role, you will collaborate with and support Solutions Architects by leveraging your hands-on production experience with large-scale data engineering and lakehouse architecture. You will help organizations navigate technical evaluations, optimize business intelligence and analytics workloads, and align their technical roadmaps with the Databricks Data Intelligence Platform.
Reporting to the Specialist Field Engineering Manager, you will serve as a deep domain expert while continuing to strengthen your technical leadership through mentorship, continuous learning, and specialized training programs.
This position can be remote.
The impact you will have:
- Guide Strategic Implementations: Provide technical leadership to help enterprise customers successfully build, scale, and optimize big data and large-scale data warehousing workloads.
- Prove Platform Value: Architect production-ready pipelines and demonstrate the power of the Databricks Data Intelligence Platform through end-to-end performance testing, load testing, and optimization.
- Deep Domain Expertise: Build expertise across specialized domains such as data lake architecture, high-velocity streaming, automated ingestion workflows, and data observability.
- Support Technical Sales: Partner with Solutions Architects on complex pre-sales engagements, including custom proofs of concept (POCs), workload sizing estimations, and custom architecture designs.
- Community & Adoption: Enable adoption by leading workshops, hackathons, and conference presentations, while actively contributing to the broader Databricks community.
What we look for:
- 8+ years of experience in a technical role with deep expertise across:
- Data & Software Engineering: Hands-on experience with streaming technologies (e.g., Spark Streaming, Kafka), batch ingestion, performance tuning, and troubleshooting complex Spark workloads.
- Data Applications Engineering: Experience building or supporting data-driven use cases, predictive analytics pipelines, or customer analytics platforms.
- Data Warehousing & Migration: Experience migrating EDW workloads (e.g., legacy SQL, Redshift, Snowflake, Synapse, EMR) across OLAP/OLTP systems; advanced query tuning, governance, and MPP debugging.
- Data Observability & Security: Telemetry, high-velocity log ingestion, anomaly detection, and familiarity with SIEM tools (e.g., Splunk, Elastic, Sentinel).
- 5+ years of experience in a customer-facing technical role (Pre-Sales, Post-Sales, or Consulting).
- Deep understanding of modern lakehouse architectures (Delta Lake, data modeling, BI integration) across major cloud platforms (AWS, Azure, or GCP).
- Production-level programming experience in SQL and at least one language among Python, Scala, or Java.
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
- [Nice to have] Databricks certifications.
- Ability to hit role-specific training and technical delivery milestones within the first 6 months.
- Willingness to travel up to 30% as needed.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.