All fields marked * are required
Key Responsibilities
Design, develop, and maintain efficient data pipelines and data processing workflows.
Write optimized and complex SQL queries for data extraction, transformation, validation, and analysis.
Develop and maintain data processing solutions using Python.
Work with large and complex datasets to ensure data accuracy, quality, and consistency.
Develop and maintain PLX dashboards and data visualizations for reporting and business insights.
Transform raw data into meaningful datasets and analytical outputs.
Troubleshoot data pipelines, queries, dashboards, and data quality issues.
Collaborate with data analysts, business teams, and other technical stakeholders to understand data requirements.
Optimize existing data workflows and queries for improved performance.
Implement data validation and quality checks across data pipelines.
Document data processes, pipelines, queries, and dashboard solutions.
4–8 years of experience in Data Engineering / Data Analytics / Data Development.
Strong hands-on experience with SQL.
Strong programming experience in Python.
Hands-on experience with PLX dashboarding and data visualization.
Good understanding of ETL/ELT concepts and data pipelines.
Experience working with large datasets and data transformation.
Strong troubleshooting and analytical/problem-solving skills.
Good understanding of data quality, validation, and optimization.
Ability to work independently in a remote environment.
Experience with cloud data platforms such as AWS, Azure, or GCP.
Knowledge of Spark/PySpark.
Experience with data warehouses and databases.
Exposure to Airflow or other workflow orchestration tools.
Experience with BI/reporting tools.
Knowledge of data modeling and performance optimization.
Required
Preferred
All fields marked * are required
Key Responsibilities
Design, develop, and maintain efficient data pipelines and data processing workflows.
Write optimized and complex SQL queries for data extraction, transformation, validation, and analysis.
Develop and maintain data processing solutions using Python.
Work with large and complex datasets to ensure data accuracy, quality, and consistency.
Develop and maintain PLX dashboards and data visualizations for reporting and business insights.
Transform raw data into meaningful datasets and analytical outputs.
Troubleshoot data pipelines, queries, dashboards, and data quality issues.
Collaborate with data analysts, business teams, and other technical stakeholders to understand data requirements.
Optimize existing data workflows and queries for improved performance.
Implement data validation and quality checks across data pipelines.
Document data processes, pipelines, queries, and dashboard solutions.
4–8 years of experience in Data Engineering / Data Analytics / Data Development.
Strong hands-on experience with SQL.
Strong programming experience in Python.
Hands-on experience with PLX dashboarding and data visualization.
Good understanding of ETL/ELT concepts and data pipelines.
Experience working with large datasets and data transformation.
Strong troubleshooting and analytical/problem-solving skills.
Good understanding of data quality, validation, and optimization.
Ability to work independently in a remote environment.
Experience with cloud data platforms such as AWS, Azure, or GCP.
Knowledge of Spark/PySpark.
Experience with data warehouses and databases.
Exposure to Airflow or other workflow orchestration tools.
Experience with BI/reporting tools.
Knowledge of data modeling and performance optimization.
Required
Preferred