Strategic Overview
Sr. Software Engineer - Ingestion Core team at Databricks is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Build distributed infrastructure to ingest data from diverse sources and support streaming ingestion, incremental processing, and replication. This isn’t just about building plugin connectors. Design and optimize streaming and distributed workloads for…
The role is listed for San Francisco, California with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
Deeply understanding what’s in the enterprise data has been a challenge that Databricks has been addressing by providing analytics and machine learning tools. From data warehousing with Databricks SQL to large-scale distributed processing with Spark and advanced ML tools for experimentation and model serving, we empower our customers to gain insights and drive innovation.
To enable all of this on Databricks, making data ingestion seamless is crucial. That’s the mission of the Ingestion Core Team: to make the ingestion of all data—structured and unstructured—simple, reliable, and efficient. Simplifying the complex is hard, and that’s where you come in. This role requires building distributed platform systems to incrementally ingest high-volume, petabyte-scale data from diverse…
Join us in making data ingestion effortless and be part of the team that powers the future of AI + data at Databricks!
Key Responsibilities & Objectives
- Build distributed infrastructure to ingest data from diverse sources and support streaming ingestion, incremental processing, and replication. This isn’t just about building plugin connectors.
- Design and optimize streaming and distributed workloads for throughput, cost, latency, reliability, and scale.
- Build monitoring and observability capabilities (customer-facing and internal) that provide visibility into ingestion workflows and the systems running them.
- Collaborate with partner teams to enable use cases like RAG and AI agents.
Required Qualifications & Candidate Blueprint
- 5+ years of experience writing production code in one of: Java, Scala, Go, C++, or Python.
- Experience with distributed systems, streaming, Spark, databases, data processing, or CDC.
Salary & Benefits
Published compensation: $166,000 – $225,000 USD
Salary Benchmark
This role’s published compensation is compared with current employer-disclosed salary ranges for the same role at the Senior level in the same currency.
Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
Deeply understanding what’s in the enterprise data has been a challenge that Databricks has been addressing by providing analytics and machine learning tools. From data warehousing with Databricks SQL to large-scale distributed processing with Spark and advanced ML tools for experimentation and model serving, we empower our customers to gain insights and drive innovation.
To enable all of this on Databricks, making data ingestion seamless is crucial. That’s the mission of the Ingestion Core Team: to make the ingestion of all data—structured and unstructured—simple, reliable, and efficient. Simplifying the complex is hard, and that’s where you come in. This role requires building distributed platform systems to incrementally ingest high-volume, petabyte-scale data from diverse sources—including cloud storage (SQS, ADLS, GCS), databases (Oracle, SQL Server, MySQL, Postgres), and file sources (Google Drive, SharePoint)—at high throughput and low cost. The data includes structured formats (JSON, Parquet, CSV) as well as unstructured data (text, images, docs, PPTs, and blobs), all of which land in Delta Lake with schema evolution and change data capture (CDC) capabilities.
Join us in making data ingestion effortless and be part of the team that powers the future of AI + data at Databricks!
As an engineer on the team, you will work on projects that:
- Build distributed infrastructure to ingest data from diverse sources and support streaming ingestion, incremental processing, and replication. This isn’t just about building plugin connectors.
- Reduce end-to-end latency, increase throughput, and reduce costs from the time data appears in source systems to when it is available in Delta Lake.
- Design and optimize streaming and distributed workloads for throughput, cost, latency, reliability, and scale.
- Optimize streaming workloads by exploring and applying ML techniques.
- Build monitoring and observability capabilities (customer-facing and internal) that provide visibility into ingestion workflows and the systems running them.
- Collaborate with partner teams to enable use cases like RAG and AI agents.
- Build Agentic SDKs with strong evaluations.
Ideal Engineer should have:
- 5+ years of experience writing production code in one of: Java, Scala, Go, C++, or Python.
- Experience architecting, developing, and deploying large-scale distributed and asynchronous systems.
- Experience with distributed systems, streaming, Spark, databases, data processing, or CDC.
- Experience building or operating systems where scale, throughput, latency, reliability, and cost are important considerations.
- Comfortable using AI tools and defining effective evals to shorten the development loop.
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Build distributed infrastructure to ingest data from diverse sources and support streaming ingestion, incremental processing, and replication. This isn’t just about building plugin connectors. — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.