Sr. Data Business Analyst - SQL / Spark / ETL / NoSQL

ICONMA LLC
Englewood, CO, United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
0 years minimum
Compensation
$80,100.0 - $120,010.0
Working hours
Regular working hours

Tech stack

Data Analysis Microsoft Azure Big Data Data Validation Data Dictionary Extract Transform Load (ETL) Data Transformation Data Stores Relational Databases Database Design Decision Support Systems NoSQL
+12 more
Performance Tuning Query Optimization Standard Sql SQL Databases Data Streaming Unstructured Data Data Processing Apache Spark Information Technology Real Time Data Database Installation Data Pipelines

Job description

Our Client, an IT Services and Consultant company, is looking for a Sr. Data Business Analyst - SQL / Spark / ETL / NoSQL for their Englewood, CO /Denver, CO/Hybrid location. Responsibilities:

  • Analyze complex business processes and data flows to define detailed requirements that guide the design of scalable data solutions aligned with enterprise objectives and regulatory expectations.
  • Translate business requirements into logical and physical data models that optimize performance, maintainability and consistency across transactional and analytical systems.
  • Coordinate end to end database installation activities by collaborating with infrastructure and application teams to ensure stable environments and reliable data availability for business operations.
  • Design and refine relational and nonrelational database schemas that support reporting, analytics and integration needs while maintaining data quality and integrity.
  • Develop and optimize SQL queries, views and stored logic to support dashboards, operational reports and ad hoc analysis with a strong focus on performance and accuracy.
  • Apply No SQL data modeling practices to support large scale semi structured or unstructured data workloads and ensure optimal access patterns for analytics and downstream consumption.
  • Define and validate ETL workflows by working with engineering teams to ensure data extraction transformation and loading steps are robust, reusable and aligned with target data models.
  • Use Spark based data processing techniques to support batch and near real time data pipelines that deliver timely insights to business stakeholders and downstream applications.
  • Document detailed functional specifications data dictionaries and source to target mappings that provide clear guidance for development testing and operations teams.
  • Collaborate with cross functional stakeholders to prioritize analytic features enhancements and defect resolutions that improve data reliability and decision support capabilities.
  • Conduct data validation and reconciliation activities to identify defects anomalies and root causes and recommend corrective actions that protect analytical accuracy and trust.
  • Provide ongoing support to business users by clarifying data definitions troubleshooting data pipeline issues and recommending enhancements that improve usability and adoption.
  • Contribute to continuous improvement initiatives by recommending standardization of database design practices ETL patterns and metric definitions that strengthen organizational data maturity.

Requirements

  • Demonstrate advanced knowledge of relational databases including design normalization indexing and query optimization supported by several years of practical project experience.
  • Show strong experience in database installation configuration and environment validation across development testing and production instances for enterprise scale systems.
  • Apply solid SQL expertise including complex joins window functions and aggregation logic to support analytical reporting and operational workloads in high volume settings.
  • Exhibit practical No SQL experience using document key value or column oriented data stores with clear understanding of appropriate use cases and modeling strategies.
  • Display hands on ETL experience across design testing and deployment using enterprise tools or frameworks while maintaining robust error handling and data validation practices.
  • Utilize Spark for data transformation and aggregation across large datasets with clear focus on performance tuning resource optimization and reliable pipeline execution.
  • Leverage analytical and communication skills gained through six to ten years of professional experience as a business analyst in data driven or technology focused organizations.
  • 60CW00 Business Associate
  • Preferred certifications include CBAP and one data focused credential such as Microsoft Azure Data Engineer Associate or equivalent.
  • Years of Experience: 10.00 Years of Experience

Benefits & conditions

  • $79,229-118,843 per year Make your mark at Comcast – a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hu…

  • 1 day ago +

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