Job
Description
Key Responsibilities Design & Implementation: Design and implement robust, scalable data engineering pipelines within GCP , specifically tailored for web analytics. Data Integration: Integrate a variety of marketing & enterprise data sources, including AWS Aurora, SAP, and Salesforce , ensuring seamless data flow and accessibility. End-to-End Project Execution: Execute at least 1-2 end-to-end data engineering projects , from conceptualization to deployment, demonstrating strong project management and technical prowess. Scripting & Optimization: Employ advanced SQL, Python, and Bash scripting to optimize data processing, analysis, and automation tasks. Cross-functional Collaboration: Collaborate with cross-functional teams to identify data needs, design effective solutions, and enhance data-driven decision-making capabilities. Data Integrity & Security: Maintain and ensure the integrity and reliability of data pipelines, implementing best practices in data security and compliance. Qualifications Education: Bachelor's/Master's in computer/allied STEM engineering fields. (BS in Mathematics, Statistics, Computer Science, Engineering, Data Science, Analytics, or related field preferred). Experience: Relevant 4-6 years of proven experience as a Data Engineer, with a specific focus on web analytics data engineering pipelines. Cloud Proficiency (GCP & AWS): Hands-on experience with GCP & AWS , including their respective data processing and analytics services. GCP Services: Pub/Sub, Dataflow, BigQuery, Cloud Functions, Cloud Run, Bigtable, etc. AWS Services: Glue, Redshift, S3, SQS, Aurora, etc. API Integration: Strong proficiency in integrating data from diverse sources using APIs . Scripting Expertise: Advanced knowledge of SQL, Python, and Bash scripting is essential. Project Execution: Demonstrated ability to execute end-to-end projects, showcasing effective project management and technical skills. Problem-Solving: Excellent problem-solving abilities, with a keen eye for detail and a commitment to high-quality outcomes. Communication: Strong communication skills, with the ability to convey complex technical concepts in a clear, concise manner.
