Data Engineer 4
Austin, Texas
Employer: INTELLISWIFT INC
Industry: Customer Job
Salary: $70 per hour
Job type: Full-Time
Job ID: 24-02606
Data Engineer
Open for remote candidates all over the US. CST preferred
12 Months
$70 per hour on W2
Client Commerce Engineering Operations is building next-generation business analytics and decision support capabilities to enable modern, data-driven engineering management and business optimization. Being data-driven is central to who we are and how we operate. We are looking for someone who deeply appreciates the power of answering business questions with data, who loves to design data to solve problems, and who loves to automate things to create game-changing insights that drive quick, informed decision-making.
The Work
Build collaborative relationships to solve problems with data.
Acquire operational domain knowledge through collaboration with management and engineering teams.
Build data solutions in Python, SQL, and Cloud-Native ETL tools to answer business questions.
Analyze data sources to implement data preprocessing and transformation/aggregation algorithms in Python.
Perform feature engineering to answer breakthrough business and operational questions.
Build visualizations in Power BI and AWS QuickSight.
Document and present ongoing work and data insight to business stakeholders.
Qualifications
5+ years of professional experience in the development, and operations of ETL and data analytics applications.
5+ years of experience building RDBMS (SQL) solutions.
3+ years of experience doing exploratory data analysis in Python (NumPy, Pandas).
3+ years of experience with AWS technologies (S3, Redshift, Glue, Lambda).
Experience building ETL data pipelines, data quality checks, and data anomaly detection and notification systems.
Experience working with CI/CD technologies and cloud infrastructure services.
Must be highly effective in written and verbal communication and be comfortable presenting problems and solution hypotheses.
Preferred Qualifications
Talend experience.
MLOps experience building, training, running, and managing machine learning models in production.
Data Engineer
Open for remote candidates all over the US. CST preferred
12 Months
$70 per hour on W2
Client Commerce Engineering Operations is building next-generation business analytics and decision support capabilities to enable modern, data-driven engineering management and business optimization. Being data-driven is central to who we are and how we operate. We are looking for someone who deeply appreciates the power of answering business questions with data, who loves to design data to solve problems, and who loves to automate things to create game-changing insights that drive quick, informed decision-making.
The Work
Build collaborative relationships to solve problems with data.
Acquire operational domain knowledge through collaboration with management and engineering teams.
Build data solutions in Python, SQL, and Cloud-Native ETL tools to answer business questions.
Analyze data sources to implement data preprocessing and transformation/aggregation algorithms in Python.
Perform feature engineering to answer breakthrough business and operational questions.
Build visualizations in Power BI and AWS QuickSight.
Document and present ongoing work and data insight to business stakeholders.
Qualifications
5+ years of professional experience in the development, and operations of ETL and data analytics applications.
5+ years of experience building RDBMS (SQL) solutions.
3+ years of experience doing exploratory data analysis in Python (NumPy, Pandas).
3+ years of experience with AWS technologies (S3, Redshift, Glue, Lambda).
Experience building ETL data pipelines, data quality checks, and data anomaly detection and notification systems.
Experience working with CI/CD technologies and cloud infrastructure services.
Must be highly effective in written and verbal communication and be comfortable presenting problems and solution hypotheses.
Preferred Qualifications
Talend experience.
MLOps experience building, training, running, and managing machine learning models in production.
Created: 2024-05-02
Reference: xDoCzVcC9Bk3
Country: United States
State: Texas
City: Austin
ZIP: 78749
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