We are seeking a highly skilled Senior Data Engineer to join our growing Data & Analytics team within a leading environmental services organization. This role will play a critical part in designing building and optimizing enterprise-scale data platforms that support financial reporting planning forecasting and strategic decision-making across the business.
The ideal candidate combines deep technical expertise in modern data engineering technologies with strong analytical capabilities and experience working with financial datasets. You will collaborate closely with finance operations business intelligence and data science teams to develop scalable data solutions that transform complex data into actionable business insights.
Key Responsibilities
Design develop and maintain scalable high-performance data pipelines that ingest transform and deliver large volumes of structured and unstructured data.
Build and optimize cloud-based data platforms and data lake architectures using AWS services and modern data engineering best practices.
Develop robust ETL/ELT processes using Python and Apache Spark to support analytics reporting and forecasting initiatives.
Partner with Finance and business stakeholders to understand reporting requirements and translate them into reliable data solutions.
Design and implement dimensional and multi-dimensional data models that support financial analysis budgeting forecasting and operational reporting.
Ensure data quality consistency governance and reliability across enterprise data assets.
Perform data profiling and exploratory data analysis (EDA) to identify trends anomalies and opportunities for improving business performance.
Collaborate with data analysts data scientists and business intelligence teams to enable advanced analytics and decision-support capabilities.
Monitor troubleshoot and optimize data workflows to ensure scalability efficiency and performance.
Contribute to the evolution of data architecture standards best practices and engineering processes.
Required Qualifications
Strong hands-on experience with Apache SparkAWS and Python in enterprise-scale data environments.
Proven track record designing building and optimizing large-scale data pipelines and modern data platforms.
Experience developing and maintaining cloud-native data solutions and distributed data processing systems.
Strong understanding of data warehousing concepts ETL/ELT methodologies and data integration practices.
Excellent problem-solving skills and the ability to work with complex datasets in a fast-paced environment.
Strong communication skills with the ability to collaborate effectively across technical and business teams.
Preferred Qualifications
Experience working with financial data including financial reporting budgeting forecasting planning revenue analysis cost management or other finance-related datasets.
Strong proficiency in exploratory data analysis (EDA) and translating business requirements into effective analytical data models.
Experience designing dimensional and multi-dimensional data models to support enterprise reporting and analytics.
Solid understanding of statistics and its application to data analysis forecasting trend identification and decision support.
Familiarity with financial performance metrics KPIs and analytical frameworks used in corporate finance environments.
Experience supporting advanced analytics predictive modeling or forecasting initiatives.
What Success Looks Like
In this role you will help establish a trusted and scalable data foundation that enables better financial visibility operational efficiency and strategic decision-making. Your work will directly support the organizations ability to analyze business performance forecast future outcomes and drive data-informed growth within the environmental services sector.
Ideal Candidate Profile: A technically strong data engineer who enjoys building scalable cloud-based data solutions and has experience working with financial data and analytics. You are equally comfortable engineering robust data pipelines modeling complex business data and partnering with stakeholders to deliver meaningful business insights.
Required Experience:
Senior IC
Senior Data Engineer (Financial Analytics & Data Platforms)Location: Flexible / HybridIndustry: Environmental ServicesDepartment: Data & AnalyticsPosition OverviewWe are seeking a highly skilled Senior Data Engineer to join our growing Data & Analytics team within a leading environmental services or...
Senior Data Engineer (Financial Analytics & Data Platforms)
We are seeking a highly skilled Senior Data Engineer to join our growing Data & Analytics team within a leading environmental services organization. This role will play a critical part in designing building and optimizing enterprise-scale data platforms that support financial reporting planning forecasting and strategic decision-making across the business.
The ideal candidate combines deep technical expertise in modern data engineering technologies with strong analytical capabilities and experience working with financial datasets. You will collaborate closely with finance operations business intelligence and data science teams to develop scalable data solutions that transform complex data into actionable business insights.
Key Responsibilities
Design develop and maintain scalable high-performance data pipelines that ingest transform and deliver large volumes of structured and unstructured data.
Build and optimize cloud-based data platforms and data lake architectures using AWS services and modern data engineering best practices.
Develop robust ETL/ELT processes using Python and Apache Spark to support analytics reporting and forecasting initiatives.
Partner with Finance and business stakeholders to understand reporting requirements and translate them into reliable data solutions.
Design and implement dimensional and multi-dimensional data models that support financial analysis budgeting forecasting and operational reporting.
Ensure data quality consistency governance and reliability across enterprise data assets.
Perform data profiling and exploratory data analysis (EDA) to identify trends anomalies and opportunities for improving business performance.
Collaborate with data analysts data scientists and business intelligence teams to enable advanced analytics and decision-support capabilities.
Monitor troubleshoot and optimize data workflows to ensure scalability efficiency and performance.
Contribute to the evolution of data architecture standards best practices and engineering processes.
Required Qualifications
Strong hands-on experience with Apache SparkAWS and Python in enterprise-scale data environments.
Proven track record designing building and optimizing large-scale data pipelines and modern data platforms.
Experience developing and maintaining cloud-native data solutions and distributed data processing systems.
Strong understanding of data warehousing concepts ETL/ELT methodologies and data integration practices.
Excellent problem-solving skills and the ability to work with complex datasets in a fast-paced environment.
Strong communication skills with the ability to collaborate effectively across technical and business teams.
Preferred Qualifications
Experience working with financial data including financial reporting budgeting forecasting planning revenue analysis cost management or other finance-related datasets.
Strong proficiency in exploratory data analysis (EDA) and translating business requirements into effective analytical data models.
Experience designing dimensional and multi-dimensional data models to support enterprise reporting and analytics.
Solid understanding of statistics and its application to data analysis forecasting trend identification and decision support.
Familiarity with financial performance metrics KPIs and analytical frameworks used in corporate finance environments.
Experience supporting advanced analytics predictive modeling or forecasting initiatives.
What Success Looks Like
In this role you will help establish a trusted and scalable data foundation that enables better financial visibility operational efficiency and strategic decision-making. Your work will directly support the organizations ability to analyze business performance forecast future outcomes and drive data-informed growth within the environmental services sector.
Ideal Candidate Profile: A technically strong data engineer who enjoys building scalable cloud-based data solutions and has experience working with financial data and analytics. You are equally comfortable engineering robust data pipelines modeling complex business data and partnering with stakeholders to deliver meaningful business insights.