Job
Description
As a Lead Data Engineer specializing in AWS Redshift, you will play a crucial role in designing, developing, and optimizing scalable ETL/ELT pipelines to facilitate efficient data integration and drive critical business intelligence and analytics initiatives. Your expertise in AWS Redshift, including a deep understanding of Redshift architecture, query performance tuning, and workload optimization, will be instrumental in ensuring that our data ecosystem is both scalable and cost-efficient. Your responsibilities will involve troubleshooting complex data challenges, implementing performance improvements, and fostering a data-driven decision-making culture within the organization. **Key Responsibilities:** - Lead the design and architecture of scalable and robust data integration solutions on-premise and in the cloud, ensuring alignment with business requirements and industry standards. - Collaborate with executive leadership and key stakeholders to translate business needs into technical solutions. - Define data models, schemas, and structures to optimize data storage, retrieval, and processing for analytical workloads. - Provide technical guidance, mentorship, and support to a team of data engineers. - Plan, prioritize, and manage data engineering projects, tasks, and timelines effectively. - Design, develop, and maintain data integration pipelines and ETL/ELT workflows. - Oversee multiple projects or manage larger teams with sub-tracks. **Qualifications Required:** - Proficient in basic and advanced SQL. - Strong programming skills in Python for data integration and data engineering tasks. - Experience with ETL/ELT tools such as Informatica, Talend, DataStage, SSIS, DBT, Databricks, or equivalent. - Hands-on experience with relational databases (SQL Server, Oracle, MySQL, PostgreSQL), NoSQL databases (MongoDB, Cassandra), and cloud databases (RedShift, Snowflake, Azure SQL). - Familiarity with big data technologies (Hadoop, Spark, Kafka) and cloud platforms (AWS, Azure, Google Cloud). - Solid understanding of data modeling, data warehousing concepts, and practices. - Knowledge of data warehouse concepts (Dimensional Modeling, change data capture, slowly changing dimensions, etc.). - Experience in performance tuning and optimization, data profiling, data validation, and requirements gathering. - Ability to adapt to a fast-paced Agile environment and willingness to learn and take initiatives. - Relevant certifications in data engineering or cloud platforms are considered a plus. The company is seeking a Lead Data Engineer with at least 8+ years of experience in ETL/ELT, preferably with Informatica IICS/Powercenter, and a minimum of 4+ years of hands-on experience with AWS Redshift. Strong proficiency in AWS Redshift and writing complex SQL queries, solid programming experience in Python, familiarity with version control tools like Git, and knowledge of data modeling and data warehousing concepts are highly valued. Prior experience with data lakes and big data technologies will be advantageous in this role. As a Lead Data Engineer specializing in AWS Redshift, you will play a crucial role in designing, developing, and optimizing scalable ETL/ELT pipelines to facilitate efficient data integration and drive critical business intelligence and analytics initiatives. Your expertise in AWS Redshift, including a deep understanding of Redshift architecture, query performance tuning, and workload optimization, will be instrumental in ensuring that our data ecosystem is both scalable and cost-efficient. Your responsibilities will involve troubleshooting complex data challenges, implementing performance improvements, and fostering a data-driven decision-making culture within the organization. **Key Responsibilities:** - Lead the design and architecture of scalable and robust data integration solutions on-premise and in the cloud, ensuring alignment with business requirements and industry standards. - Collaborate with executive leadership and key stakeholders to translate business needs into technical solutions. - Define data models, schemas, and structures to optimize data storage, retrieval, and processing for analytical workloads. - Provide technical guidance, mentorship, and support to a team of data engineers. - Plan, prioritize, and manage data engineering projects, tasks, and timelines effectively. - Design, develop, and maintain data integration pipelines and ETL/ELT workflows. - Oversee multiple projects or manage larger teams with sub-tracks. **Qualifications Required:** - Proficient in basic and advanced SQL. - Strong programming skills in Python for data integration and data engineering tasks. - Experience with ETL/ELT tools such as Informatica, Talend, DataStage, SSIS, DBT, Databricks, or equivalent. - Hands-on experience with relational databases (SQL Server, Oracle, MySQL, PostgreSQL), NoSQL databases (MongoDB, Cassandra), and cloud databases (RedShift, Snowflake, Azure SQL). - Familiarity with big da
