Data Engineer

What You'll Do:

• The Data Engineer role involves the following responsibilities:
Data Collection and Integration:
• Identify and evaluate relevant data sources, both internal and external, to support site work cost estimation and project feasibility analysis.
• Design and implement data collection strategies, ensuring data quality, consistency, and integrity.
• Develop and maintain data pipelines, leveraging ETL (Extract, Transform, Load) processes to efficiently integrate data from multiple sources.
Data Modeling and Analysis:
• Collaborate with data scientists and domain experts to understand requirements and develop data models that support site work cost estimation and project feasibility analysis.
• Design and implement scalable and efficient algorithms to extract insights from complex datasets.
• Apply statistical methods and machine learning techniques to develop predictive models that estimate site work costs and assess project feasibility.
Data Infrastructure and Optimization:
• Build and maintain scalable and robust data infrastructure, including data warehouses, databases, and data processing systems.
• Identify and implement improvements to enhance data pipeline efficiency, data quality, and overall system performance.
• Monitor data pipelines, proactively identifying and resolving issues to ensure uninterrupted data flow.
Collaboration and Communication:
• Work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to understand requirements and deliver high-quality data solutions.
• Communicate complex technical concepts and findings to non-technical stakeholders effectively.
• Stay up-to-date with industry trends and advancements in data engineering, sharing knowledge and insights with the team.

What You Have:

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
• Proven experience (2+ years) as a Data Engineer or similar role, working with large datasets and building data pipelines.
• Strong programming skills in languages such as Python, SQL, and Scala.
• Proficient in working with databases and data warehousing technologies (e.g., SQL, NoSQL, PostgreSQL, Amazon Redshift).
• Familiarity with data processing frameworks and tools (e.g., Apache Spark, Hadoop, Airflow).
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of statistical analysis, machine learning, and data modeling techniques.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.