Data Engineer

Skills:

– Data Warehousing applications

– ETL

– IBM

– AWS Infrastructure tools (EBS, S3, EC2, Elastic IP, Route 53, VPC)

– Cloud infrastructure Management and automation technologies

Must have:

– Proven expertise in designing, developing, and deploying ETL workflows using IBM Infosphere DataStage within large-scale data warehousing environments.

– Hands-on experience with AWS cloud infrastructure, including services such as EC2, S3, EBS, VPC, Route 53, and Elastic IP, for scalable and secure data solutions.

– Strong knowledge of data pipeline development, including extraction, transformation, and loading (ETL) of structured, semi-structured, and unstructured data.

– Proficient in SQL and PL/SQL programming, including writing stored procedures, functions, and complex queries for data transformation and validation.

– Adept at Unix shell scripting for process automation, job scheduling, and system monitoring.

– Exposure to modern data architectures, including big data and cloud-based analytics platforms.

– Familiar with advanced analytics tools such as Python and R for data exploration and statistical analysis.

– Skilled in ETL performance tuning and optimization for high-volume data processing and real-time reporting needs.

– Experienced with relational databases including Oracle, DB2, SQL Server, and Teradata.

– Knowledge of data profiling and quality assessment using Information Analyzer and basic exposure to QualityStage.

– Expertise in building complex transformations in DataStage using Transformers, Joins, Lookups, Aggregators, Routines, and more.