Analytics Engineer
The position of Analytics Engineer entails a blend of technical expertise and business acumen.
Analytics engineers are responsible for modeling raw data into clean and reusable datasets, applying transformations to ensure data relevance, maintaining data documentation for consistency, defining data quality rules and standards, and implementing software engineering best practices.
They also engage in data visualization, collaborate closely with team members, and contribute to aligning business requirements with data assets.
Analytics engineers play a crucial role in driving data-driven decision-making, ensuring data quality, and facilitating the accessibility and understanding of data within an organization.
Data Transformation and Modeling:
Develop and implement logic for transforming raw data into clean, tested, and reusable datasets.
Build data models to facilitate understanding and accessibility of data for business analysts and stakeholders.
Apply SQL expertise to write queries and create data transformations.
Programming and Data Orchestration:
Utilize programming languages for advanced data orchestration tasks.
Leverage knowledge of software engineering best practices to develop high-quality analytics code.
Version Control and Collaboration:
Utilize Git for version control to track changes made to data and enable collaboration with multiple users.
Ensure data integrity and facilitate teamwork by effectively managing changes and maintaining data quality.
Microsoft Data Platform:
Demonstrate proficiency in Microsoft data engineering tools, including Azure Synapse Analytics (formerly SQL Data Warehouse), Azure Data Factory, and Azure Databricks.
Utilize these tools to build data pipelines, perform data integration, and implement data transformations.
Microsoft BI Stack:
Familiarity with Microsoft Business Intelligence (BI) tools such as Power BI, SQL Server Reporting Services (SSRS), and SQL Server Analysis Services (SSAS).
Use these tools to create interactive dashboards, reports, and perform data analysis.
Strong SQL Proficiency:
Possess strong SQL skills to perform data transformations, write complex queries, and build efficient data models.
Proficiency in SQL is essential for effective data manipulation and analysis.
Interpersonal and Communication Skills:
Demonstrate excellent interpersonal skills and effective communication to collaborate with team members, stakeholders, and business clients.
Ask insightful questions and communicate data requirements and insights clearly and concisely.
Work in cross-functional teams to gather and document software and reporting requirements.
Plan and prioritize work to ensure business needs will be met promptly Perform other duties as assigned in support of team efforts and results.
REQUIRED QUALIFICATIONS AND
Experience:
Bachelor's degree in computer science or equivalent field.
Minimum three years of work history in relevant application development, and integration environment.
Strong background in data management, software development, and relational databases required.
Experience writing and optimizing SQL queries.
Knowledge of algorithms and data structures Strong Experience and working knowledge of Python, C#, and JavaScript.
Strong DevOps focus and experience building and deploying infrastructure with cloud deployment technologies.
Strong documentation skills using GitHub, Azure DevOps, Teams, and similar tools.
Preferred
Experience:
Azure, SSMS, and PowerBI.
Professional written and verbal communication skills.
Ability to work in a face-to-paced environment and solve complex problems.
%56903903% %% category %% Recommended Skills Algorithms Business Requirements C Sharp (Programming Language) Commercial Awareness Dashboard Data Analysis Estimated Salary: $20 to $28 per hour based on qualifications.
Analytics engineers are responsible for modeling raw data into clean and reusable datasets, applying transformations to ensure data relevance, maintaining data documentation for consistency, defining data quality rules and standards, and implementing software engineering best practices.
They also engage in data visualization, collaborate closely with team members, and contribute to aligning business requirements with data assets.
Analytics engineers play a crucial role in driving data-driven decision-making, ensuring data quality, and facilitating the accessibility and understanding of data within an organization.
Data Transformation and Modeling:
Develop and implement logic for transforming raw data into clean, tested, and reusable datasets.
Build data models to facilitate understanding and accessibility of data for business analysts and stakeholders.
Apply SQL expertise to write queries and create data transformations.
Programming and Data Orchestration:
Utilize programming languages for advanced data orchestration tasks.
Leverage knowledge of software engineering best practices to develop high-quality analytics code.
Version Control and Collaboration:
Utilize Git for version control to track changes made to data and enable collaboration with multiple users.
Ensure data integrity and facilitate teamwork by effectively managing changes and maintaining data quality.
Microsoft Data Platform:
Demonstrate proficiency in Microsoft data engineering tools, including Azure Synapse Analytics (formerly SQL Data Warehouse), Azure Data Factory, and Azure Databricks.
Utilize these tools to build data pipelines, perform data integration, and implement data transformations.
Microsoft BI Stack:
Familiarity with Microsoft Business Intelligence (BI) tools such as Power BI, SQL Server Reporting Services (SSRS), and SQL Server Analysis Services (SSAS).
Use these tools to create interactive dashboards, reports, and perform data analysis.
Strong SQL Proficiency:
Possess strong SQL skills to perform data transformations, write complex queries, and build efficient data models.
Proficiency in SQL is essential for effective data manipulation and analysis.
Interpersonal and Communication Skills:
Demonstrate excellent interpersonal skills and effective communication to collaborate with team members, stakeholders, and business clients.
Ask insightful questions and communicate data requirements and insights clearly and concisely.
Work in cross-functional teams to gather and document software and reporting requirements.
Plan and prioritize work to ensure business needs will be met promptly Perform other duties as assigned in support of team efforts and results.
REQUIRED QUALIFICATIONS AND
Experience:
Bachelor's degree in computer science or equivalent field.
Minimum three years of work history in relevant application development, and integration environment.
Strong background in data management, software development, and relational databases required.
Experience writing and optimizing SQL queries.
Knowledge of algorithms and data structures Strong Experience and working knowledge of Python, C#, and JavaScript.
Strong DevOps focus and experience building and deploying infrastructure with cloud deployment technologies.
Strong documentation skills using GitHub, Azure DevOps, Teams, and similar tools.
Preferred
Experience:
Azure, SSMS, and PowerBI.
Professional written and verbal communication skills.
Ability to work in a face-to-paced environment and solve complex problems.
%56903903% %% category %% Recommended Skills Algorithms Business Requirements C Sharp (Programming Language) Commercial Awareness Dashboard Data Analysis Estimated Salary: $20 to $28 per hour based on qualifications.
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