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Full Stack Data Engineer and Analytics Developer
Cynet Systems
- United States
- United States
About
Requirement/Must Have:
Bachelor's degree in Business, Data Science, Computer Science, Statistics, or related field. 3+ years of experience in data analytics, full stack development, or similar hybrid roles. dvanced Power BI skills including DAX, data modeling, and report optimization. Strong SQL skills including joins, CTEs, and subqueries with experience in Postgres and Snowflake. Strong programming skills in Python including pandas, NumPy, matplotlib, seaborn. Hands-on experience with Flask and SQLAlchemy. Frontend experience using JavaScript, React, Ag-Grid, HTML, and CSS. bility to communicate complex analytical findings to non-technical stakeholders. Experience:
Experience with data warehousing and ETL processes. Web development experience using Ajax, HTML, CSS, and JavaScript. Responsibilities:
Develop, maintain, and optimize interactive dashboards and reports using Power BI. Collaborate with cross functional teams to translate business objectives into analytical and technical solutions. Extract, manipulate, and analyze large datasets using SQL and Python. Build and maintain backend services using Python Flask and SQLAlchemy. Develop and enhance front-end interfaces using JavaScript, React, Ag-Grid, and CSS. Identify trends, patterns, and anomalies to support strategic decision making. Build and maintain data pipelines and integrations ensuring data integrity, performance, and reliability. Conduct ad hoc analysis to support operational and strategic initiatives. Present technical and analytical insights clearly to stakeholders. Stay current with emerging tools, frameworks, and best practices in analytics and full stack development. Should Have:
Familiarity with version control tools such as Git. Exposure to business domains including finance, marketing, operations, or sales analytics. Knowledge of machine learning or predictive modeling. Experience with PHP, ThoughtSpot, or Sigma Computing is a plus. Skills:
Power BI and DAX. SQL (Postgres, Snowflake). Python, Flask, SQLAlchemy. JavaScript, React, Ag-Grid, HTML, CSS. Data analytics and visualization. Strong communication and presentation skills. Qualification and Education:
Bachelor's degree in Business, Data Science, Computer Science, Statistics, or related discipline.
Languages
- English
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