Job Description:
We are seeking a talented and experienced Virtual Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines and infrastructure to support our data analytics and business intelligence initiatives. Your expertise in data processing, ETL (Extract, Transform, Load) processes, and database management will be crucial in ensuring the reliability, scalability, and performance of our data systems.
Responsibilities:
- Design, develop, and maintain scalable and efficient data pipelines to ingest, process, and transform data from various sources, including databases, APIs, and streaming platforms
- Implement ETL (Extract, Transform, Load) processes to cleanse, validate, and transform raw data into usable formats for analysis and reporting, ensuring data quality and integrity throughout the process
- Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements, define data models, and implement solutions to meet business needs
- Build and optimize data warehouses, data lakes, and other storage solutions to store and organize large volumes of structured and unstructured data, ensuring accessibility, security, and performance
- Develop and maintain data processing pipelines using programming languages such as Python, SQL, or Java, as well as data processing frameworks and tools such as Apache Spark, Kafka, or Airflow
- Perform data profiling, analysis, and troubleshooting to identify and resolve data quality issues, performance bottlenecks, and other data-related challenges
- Monitor and optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness, implementing automation and optimization techniques to improve efficiency and reliability
- Ensure compliance with data governance policies, privacy regulations, and best practices in data management and security, implementing controls and safeguards to protect sensitive data
- Stay informed about emerging technologies, trends, and best practices in data engineering, and proactively recommend and implement updates and enhancements to our data systems and processes
- Document technical specifications, data workflows, and system configurations, and provide training and support to team members on data engineering concepts and tools
Requirements
- Proven experience in data engineering roles, with a strong background in designing, building, and maintaining data pipelines and infrastructure
- Proficiency in programming languages such as Python, SQL, or Java, as well as experience with data processing frameworks and tools such as Apache Spark, Kafka, or Airflow
- Solid understanding of database systems, data modeling, and database management systems (DBMS), with experience working with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra)
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud, and experience with cloud-based data services and tools (e.g., Amazon Redshift, Google BigQuery, Azure Data Lake)
- Strong problem-solving and analytical skills, with the ability to understand complex data requirements and translate them into scalable and maintainable solutions
- Excellent communication and collaboration skills, with the ability to work effectively within a distributed team and across different time zones
- Bachelors degree or equivalent experience in computer science, data engineering, or a related field is preferred
- Availability to work during US business hours, with flexibility to accommodate occasional meetings, deadlines, or project milestones outside of standard hours
