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Mid-tier consultancy, metro location, and generalist data+PowerBI requirements create moderate applicant competition.
Core data engineering skills are transferable, but finance domain experience slightly increases domain specificity.
Mandatory dbt, Snowflake, Power BI, and advanced SQL make hiring filters strict.
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Own end-to-end data engineering and analytics tasks including building SQL/dbt transformation pipelines and Power BI dashboards.
Develop, maintain, and optimize data pipelines, analytic data models, and reporting solutions to support investment analytics.
Investigate, troubleshoot, and resolve data quality and pipeline issues independently, delivering production-ready solutions in a fast-paced environment.
Strong hands-on experience with SQL, dbt, and Power BI (including DAX and dashboard development).
Experience with data modeling concepts including dimensional modeling, fact/dimension structures, and analytics datasets.
Familiarity with modern cloud data warehouses, preferably Snowflake.
Work Experience Required: Not explicitly mentioned in the JD
Experienced in both data engineering and analytics/reporting roles with a data-first, hands-on approach.
Capable of rapidly understanding and operating within an existing complex data environment with minimal supervision.
Comfortable owning tasks end-to-end from data ingestion and transformation to delivering finalized dashboards and reports.