Data Analyst

CapTech’s Data Analysts work within a collaborative, team environment to help define and deliver innovative solutions to our clients. At the intersection of data and strategy, Data Analysts play a key role in capturing requirements, designing business processes and data models, and delivering actionable data to stakeholders. Data Analysts are passionate about interpreting data to help our clients make informed decisions and they are driven by a desire to solve our clients’ most complex business problems. Data Analysts work alongside like-minded peers who share their commitment to excellence and with visionary leaders who are invested in their success.

Specific job responsibilities will vary by project role, but may include:

• Quantify ambiguous business problems by analyzing business processes, data, and systems and gathering data requirements from clients
• Implement data governance best practices by capturing data definitions, identifying data stewards, and data transformations through source-to-target mappings
• Develop data collection systems, implement databases and analytics to optimize efficiency
• Conduct data quality analysis and provide recommendations for effective quality assurance processes that improve data health
• Interpret data and analyze results using statistical techniques that provide valuable insights and guide decision making across the business
• Develop reports using modern data visualization tools and best practices to surface valuable insights to end-users
• Communicate with all levels of stakeholders as appropriate, including executives, data modelers, application developers, business users, and customers to build solutions and interpret results
• Collaborate with other data workstreams (Data Engineers, Data Architects, Data Scientists, Product Owners) on specific projects

Requirements

Typical experience for successful candidates includes:

• Experience working in an Agile development environment, including requirements definition and testing
• Knowledge of statistics and experience using statistical languages and packages for analyzing large datasets
• Demonstrable experience in the design of data models, database design development, data profiling, and various data analysis tools
• Demonstrable experience with ETL/ELT, data ingestion, and data munging/wrangling
• Experience in communicating concepts to both business and technical audiences
• Excellent interpersonal, collaboration, communication, and leadership skills

Skills

Successful candidates usually have demonstrable experience with technologies in some of these categories:

• Languages: SQL, Python, R
• Database: Hive, Snowflake, SQL Server, Oracle, Teradata, Aurora, DynamoDB, Cosmos, MongoDB, Cassandra
• Additional Technologies: dbt, Spark, FiveTran, Databricks, PowerBI, Tableau, git