Data Engineer

Role:Data Engineer

Location- Phoenix, AZ-3m days/week (Hybrid) Duration:6+ Months

Must Haves:

• Need specific engineering experience within GCP (google cloud), must do design work
• Big Query (required) Python, Pyspark
• The team will work within Lumi (AMEX internal GCP Platform) and utilize the suite of google services
• Looking for 5-7+ years of experience

Key Responsibilities: Design and develop solutions using Bigdata tools and technologies like MapReduce, Hive, Spark etc. Extensive hands-on experience in object-oriented programming using Python, PySpark APIs etc. Experience in building data pipelines for huge volume of data. Experience in designing, implementing, and managing various ETL job execution flows. Experience in implementing and maintaining Data Ingestion process. Hands on experience in writing basic to advance level of optimized queries using HQL, SQL & Spark. Hands on experience in designing, implementing, and maintaining Data Transformation jobs using most efficient tools/technologies. Ensure the performance, quality, and responsiveness of solutions. Participate in code reviews to maintain code quality. Should be able to write shell scripts. Utilize Git for source version control. Set up and maintain CI/CD pipelines. Troubleshoot, debug, and upgrade existing application & ETL job chains.  Required Skills and Qualifications: Bachelor’s degree in Computer Science Engineering, or a related field. Proven experience as Data Engineer or similar role. Strong proficiency in Object Oriented programming using Python. Experience with ETL jobs design principles. Solid understanding of HQL, SQL and data modelling. Knowledge on Unix/Linux and Shell scripting principles. Familiarity with Git and version control systems. Experience with Jenkins and CI/CD pipelines. Knowledge of software development best practices and design patterns. Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills. Experience with cloud platforms such as Google Cloud.