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Data Jobs in San Ramon, CA (NOW HIRING)

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$51.4K

$184.4K

$272.1K

How much do data jobs pay per year?

As of Aug 8, 2026, the average yearly pay for data in San Ramon, CA is $184,411.00, according to ZipRecruiter salary data. Most workers in this role earn between $149,200.00 and $190,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data analyst, and why are they important?

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with data analysis tools like Excel, SQL, Python, and visualization platforms such as Tableau or Power BI is often required, and certifications in these tools can be advantageous. Attention to detail, critical thinking, and effective communication skills help analysts interpret data accurately and present actionable insights to stakeholders. These skills are crucial for transforming raw data into meaningful information that drives informed business decisions.

How does a data analyst typically collaborate with other departments within an organization?

Data Analysts frequently work cross-functionally, partnering with teams such as marketing, finance, operations, and product development. They gather requirements from stakeholders, interpret data to provide actionable insights, and often present findings in meetings or reports tailored to the audience's needs. Effective communication is key, as analysts must translate complex data into clear, impactful recommendations that guide business decisions. This collaborative environment fosters both learning and professional growth, as Data Analysts gain exposure to various business functions.

Is it hard to get a data job?

Getting a data job can be competitive, as it often requires strong skills in data analysis, programming, and tools like SQL or Python. Relevant experience, certifications, and a solid portfolio can improve chances of securing a position in this field.

What are different jobs that work with data?

Many different jobs require you to work with data. Occupational health and safety engineers, for instance, assess safety data collected by technicians and specialists and then design new processes to mitigate observed risks. Many careers in medical research, such as running clinical trials or developing new pharmaceuticals, require data collection and analysis. A large number of government labor and economic forecasting positions employ statisticians who analyze and model data based on surveys or raw information, such as the census or employment records.

What are careers in data?

Careers in data include roles such as data analyst, data scientist, data engineer, and database administrator. These jobs involve collecting, analyzing, and interpreting data to support decision-making, often requiring skills in programming, statistics, and data visualization tools like SQL, Python, or R.

What is the difference between Data vs Data Analyst?

AspectDataData Analyst
Required CredentialsTypically a degree in computer science, information technology, or related fieldsSame as Data, often requiring a degree in statistics, data science, or related areas
Work EnvironmentData professionals work in IT, data engineering, or database management settingsData analysts work in business, finance, marketing, and similar industries analyzing data for insights
Employer & Industry UsageUsed across tech, finance, healthcare, and more for data management and infrastructureCommonly employed in business sectors to interpret data and support decision-making

Data professionals focus on managing, storing, and processing data, while Data Analysts interpret and analyze data to generate insights. Both roles require similar educational backgrounds but differ in their primary functions within organizations.

What are the most commonly searched types of Data jobs in San Ramon, CA? The most popular types of Data jobs in San Ramon, CA are:
What are popular job titles related to Data jobs in San Ramon, CA? For Data jobs in San Ramon, CA, the most frequently searched job titles are:
What job categories do people searching Data jobs in San Ramon, CA look for? The top searched job categories for Data jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Data jobs? Cities near San Ramon, CA with the most Data job openings:
Infographic showing various Data job openings in San Ramon, CA as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $184,411 per year, or $88.7 per hour.

Data Architect, Data Foundry

Initial Therapeutics, Inc.

San Francisco, CA • On-site

$132 - $193.60/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Job description

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life‑changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

Position: Data Architect, Data Foundry Location: San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN Overview

Lilly Small Molecule Discovery is purpose‑built to create molecules that make life better for people. Discovery Technology and Platforms (DTP) accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities.

Data Foundry is a multidisciplinary team within DTP that enables AI‑native drug discovery through four integrated pillars: Architecture4Insight (data infrastructure and scientific software), Methods4Insight (analytical and computational methods), Automation & Scale4Insight (lab automation and agentic workflows), and Preparedness4Insight (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI‑driven capabilities—serving both human scientists and autonomous AI agents.

Position Summary

We are seeking Data Architects at multiple levels to design and build the data infrastructure that makes AI‑native drug discovery possible. You will create the schemas, ontologies, data models, knowledge graphs, and platform architectures that transform raw scientific data into machine‑actionable, FAIR‑compliant, insight‑ready assets—serving both discovery scientists and autonomous AI agents.

This role is the foundation of Architecture4Insight. Everything the software engineering team builds—pipelines, APIs, prototypes—depends on the data models and platform architecture this team designs. You will work with deep knowledge of scientific data (chemical, biological, HTE, automation‑generated) to create custom‑fit solutions, then partner with Tech@Lilly to scale and maintain them. The role spans three focus areas depending on expertise: data modeling & ontologies, data platform & lakehouse architecture, and knowledge graph & specialized data systems.

Responsibilities Data Modeling & Ontologies
  • Design and implement data models, schemas, and ontologies for chemical, biological, and automation‑generated data that serve discovery workflows across the portfolio.
  • Define and maintain controlled vocabularies, metadata standards, and FAIR‑compliant data frameworks in partnership with Preparedness4Insight.
  • Implement semantic data standards (RDF, OWL, SPARQL) and ontology engineering practices to create interoperable, machine‑readable scientific data.
Data Platform & Lakehouse Architecture
  • Design and implement data lakehouse architecture using modern platforms (Databricks, Snowflake, or equivalent), including data storage patterns, partitioning strategies, and query optimization.
  • Build and optimize ETL/ELT pipelines using Spark, dbt, or similar tools to transform raw scientific data into analytical and ML‑ready formats.
  • Implement real‑time and streaming data integration (Kafka, Kinesis, event‑driven patterns) connecting LIMS, instruments, and lab automation systems to the data infrastructure.
Knowledge Graph & Specialized Data Systems
  • Design and implement knowledge graphs (Neo4j, Amazon Neptune, TigerGraph) that capture molecular, target, pathway, and experimental relationships across the discovery landscape.
  • Architect specialized data solutions: array databases (TileDB) for genomics/imaging, document stores (MongoDB) for experimental records, and vector databases for embedding‑based retrieval supporting ML and RAG workflows.
  • Build query and traversal patterns that enable scientists and AI agents to ask relational questions across the entire data landscape.
Cross‑Functional Partnership
  • Partner with scientific software engineers to ensure data architectures are implementable, performant, and well‑documented.
  • Collaborate with Methods4Insight to design data structures that support analytical model training, deployment, and evaluation.
  • Work with Tech@Lilly to define scaling strategies, ensure enterprise compliance, and transition data architectures to production‑grade management.
  • Contribute to build‑versus‑buy‑versus‑adopt decisions by evaluating commercial and open‑source data platforms against Data Foundry requirements.
Basic Requirements
  • B.S. or M.S. in Computer Science, Data Science, Bioinformatics, Computational Biology, Information Science, or related STEM field; Ph.D. valued for ontology and knowledge graph roles.
  • B.S. with 7+ years and M.S. with 5+ years of data architecture, data engineering, or scientific informatics experience.
  • SQL skills and experience in multiple database paradigms (relational, graph, document, columnar, key‑value).
  • Qualified applicants must be authorized to work in the United States on a full‑time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F‑1 CPT, F‑1 OPT, F‑1 STEM OPT, J‑1, H‑1B, TN, O‑1, E‑3, H‑1B1, or L‑1.
Preferred Qualifications
  • Expertise in at least one of: data modeling/ontologies, data platform engineering (Databricks, Snowflake, Spark), or graph/specialized databases (Neo4j, Neptune, MongoDB).
  • Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data integration patterns.
  • Understanding of scientific data types and experimental workflows in life sciences or pharma (chemical, biological, HTE data).
  • Strong communication skills with ability to translate data architecture concepts for both technical and scientific audiences.
  • Pharmaceutical or biotech research industry experience, particularly in discovery data management or research informatics.
  • Experience with semantic web technologies: RDF, OWL, SPARQL, Protégé, or equivalent ontology engineering tools.
  • Hands‑on experience with graph databases (Neo4j, Neptune, TigerGraph) and knowledge graph design patterns for scientific data.
  • Data lakehouse architecture experience: Databricks (Delta Lake, Unity Catalog), Snowflake, or equivalent; ETL/ELT with Spark, dbt.
  • Experience with streaming/real‑time data platforms (Kafka, Kinesis, Flink) and event‑driven architectures.
  • Familiarity with LIMS, ELN systems (e.g., Benchling), and laboratory instrument data integration.
  • Experience with vector databases (Pinecone, Weaviate, pgvector) and embedding‑based retrieval for ML/RAG applications.
  • Array database experience (TileDB, Zarr) for genomics, imaging, or high‑dimensional scientific data.
  • Experience with bioinformatics data formats (FASTA, BAM/CRAM, VCF) and biological sequence databases; familiarity with NGS data pipelines and proteomics data management.
  • FAIR data principles implementation experience and Data Readiness Level frameworks.
  • Scientific data standards and controlled vocabularies in chemistry (InChI, SMILES) or biology (Gene Ontology, UniProt, pathway databases such as Reactome or KEGG).

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form https://careers.lilly.com/us/en/workplace-accommodation for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women’s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $132,000 - $193,600. Full‑time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company‑sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well‑being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities). Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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