Analyst, Field Engineering
Databricks is looking for a Product Data Analyst to join the Digital Self Service team in Field Engineering. You will report to the Senior Director of Digital Self-Service. We're building our Self-service team to grow the adoption of data engineering, data science, machine learning, and deep learning technologies.
You have product growth experience and enjoy discovering patterns in customer data to understand gaps in the conversion funnel from sign-up to trial to commit. If you have led product analytics and customer research this opportunity will be exciting for you. You'd create analyses and data-informed designs. You'd develop the business model strategy, automate customer segmentation and attribution modeling.
You'd be our champion in making Databricks simple! You would build impact reporting and help develop data-driven design solutions.
The impact you will have:
Maintain the source of truth for self-service metrics to support monthly/quarterly reviews and ad hoc reporting.
Extract data from multiple sources to create standardized tables in the data lake.
Build dashboards to better understand our performance and gain insights.
Develop an understanding of Databricks' business and internal data model.
Establish best practices around data model governance, data sharing, and scalable reporting in partnership with Finance, Sales Operations, Product and Data Science.
What we look for:
Bachelor's Degree in Computer Science, Engineering, Operations Research, Economics, or comparable quantitative field.
6+ years of operations, finance, consulting, or engineering experience; familiarity with the software industry (and SaaS).
Expert in SQL; Experienced in Python or R.
Data Science: - Python including all standard ML, DL libraries - BigData: Spark, AWS S3 and EC2, SQL
Experience using version control like Git to work on team projects.
Proficient in excel (can write advanced macros) or Google Sheets.
Transform datasets to create meaningful visualizations/reports/dashboards using Databricks, Tableau, or comparable software packages.
Comfort managing large datasets using relational databases and automating workflows (e.g., cleaning and manipulating data from multiple sources).
Identify and address business issues and prescribe technical recommendations to partners.
Familiarity with systems such as Salesforce, integration of 3rd party tools, connecting user and account level to product usage.
Financial Reporting: - DCF, Sensitivity Analysis, Forecasting- Tools: Excel, Tableau, SFDC
Modeling: PCA, SVD, NMF- NLP Deep Learning: CNNs, RNNs, LSTM w/ word embeddings
Databricks is the data and AI company. More than 9,000 organizations worldwide — including Comcast, Condé Nast, and over 50% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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.
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.