Senior Databricks Data Analyst

New

StitchMarketing analytics

Workable workplace: remote; Workable locations: United StatesFull-TimeSenior

Salary not disclosed

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Job Details

Experience: 5+ years of experience in data analytics, analytics engineering, or business intelligence; 1+ years of hands-on experience with Databricks or a comparable cloud data platform.
Required Skills: PythonSQLMicrosoft Power BISnowflakeTableauBigQueryRedshiftDatabricksPySpark

Have 5+ years of experience in data analytics, analytics engineering, or business intelligence, with hands-on SQL as a core part of the role.
Have 1+ years of hands-on experience with Databricks or a comparable cloud data platform such as Snowflake, BigQuery, or Redshift.
Write SQL queries against large datasets independently.
Have experience with SQL warehouses, Unity Catalog, and notebooks or equivalent.
Have enough data engineering knowledge to connect data sources, set up basic ingestion, and work with bronze, silver, and gold data layers.
Have experience building dashboards and reporting in Databricks AI/BI, Power BI, Tableau, or an equivalent platform.
Understand analytics data design patterns such as star schema.
Demonstrate a track record of turning analysis into recommendations that changed a business decision.
Have client-facing experience within an agency or consultancy.
Independently interpret data in the context of a client's business and drive recommendations to completion.
Manage billable targets of 36+ hours per week and travel up to 20% for client meetings, workshops, and onsite engagements.
Marketing, CRM, or customer data experience is preferred; Python (PySpark or pandas) and Databricks certification are pluses.

Query and analyze client data in Databricks using SQL and, where needed, Python across silver and gold layers.
Connect data sources, set up simple ingestion, and partner with data engineers on complex pipeline builds.
Build and maintain dashboards, reporting, and Genie spaces for client marketers.
Interpret data and present prioritized recommendations to marketing and data stakeholders.
Build support for recommendations, align stakeholders, and follow through until changes are implemented and measured.
Design KPI frameworks, segmentation and lifecycle strategies, and support identity and customer 360 work.
Profile data sources, validate data quality, and test customer identity and 360 outputs with data engineers.
Reconcile audiences and data between Databricks and activation platforms such as Braze, and investigate count discrepancies.
Run data audits and readiness assessments and present findings to client marketing, data, and IT leaders.
Partner with project managers, architects, and data engineers; contribute reusable queries, dashboard templates, assessment tools, and analytics accelerators.

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