Lead Data Engineer with AWS OpenSearch

As a Data Engineering Lead at GlobalLogic, you will be responsible for driving the design, development, and optimization of robust, scalable, and secure data pipelines and platforms using AWS OpenSearch. Your role will involve shaping the organization's data strategy, leading high-performance engineering teams, and delivering data infrastructure to support analytics, AI/ML, and business intelligence initiatives. **Key Responsibilities:** - Lead the data engineering team in developing and maintaining data pipelines, data lakes, and data warehouses across structured and unstructured data sources. - Architect and implement scalable, fault-tolerant, and secure data platforms in cloud environments like AWS, Azure, or GCP. - Design and optimize ETL/ELT processes using modern tools and technologies such as Apache Spark, Apache Airflow, dbt, Kafka, and Glue. - Build and maintain real-time and batch data processing systems, ensuring data quality, accuracy, and lineage. - Collaborate with data scientists, analysts, and business teams to enable data democratization and self-service analytics. - Implement data governance, security, compliance, and metadata management frameworks. - Lead technical design reviews, provide architectural guidance, and mentor data engineers on best practices and emerging technologies. **Qualifications:** - Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related technical field. - 12+ years of experience in data engineering or software engineering with a strong data focus. - Proven expertise in designing and building distributed data platforms and processing frameworks at scale. - Strong programming skills in Python, Java, or Scala and expertise in SQL. - Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, Presto, or Hive. - Deep knowledge of data modeling, data warehousing (e.g., Snowflake, Redshift, BigQuery), and cloud-native databases. - Experience working with cloud platforms (AWS, GCP, Azure) and managed data services. - Experience with orchestration and workflow tools like Apache Airflow, Luigi, or Prefect. - Strong understanding of data governance, lineage, cataloging, and security practices. - Ability to lead cross-functional technical teams, conduct code reviews, and define coding standards and practices. At GlobalLogic, you'll experience a culture of caring, where people are prioritized, and continuous learning and development are encouraged. You'll have the opportunity to work on interesting and meaningful projects with a high-trust organization that values integrity and trust. Join us to be a part of a team that engineers impact and collaborates with clients worldwide to create innovative digital solutions. As a Data Engineering Lead at GlobalLogic, you will be responsible for driving the design, development, and optimization of robust, scalable, and secure data pipelines and platforms using AWS OpenSearch. Your role will involve shaping the organization's data strategy, leading high-performance engineering teams, and delivering data infrastructure to support analytics, AI/ML, and business intelligence initiatives. **Key Responsibilities:** - Lead the data engineering team in developing and maintaining data pipelines, data lakes, and data warehouses across structured and unstructured data sources. - Architect and implement scalable, fault-tolerant, and secure data platforms in cloud environments like AWS, Azure, or GCP. - Design and optimize ETL/ELT processes using modern tools and technologies such as Apache Spark, Apache Airflow, dbt, Kafka, and Glue. - Build and maintain real-time and batch data processing systems, ensuring data quality, accuracy, and lineage. - Collaborate with data scientists, analysts, and business teams to enable data democratization and self-service analytics. - Implement data governance, security, compliance, and metadata management frameworks. - Lead technical design reviews, provide architectural guidance, and mentor data engineers on best practices and emerging technologies. **Qualifications:** - Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related technical field. - 12+ years of experience in data engineering or software engineering with a strong data focus. - Proven expertise in designing and building distributed data platforms and processing frameworks at scale. - Strong programming skills in Python, Java, or Scala and expertise in SQL. - Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, Presto, or Hive. - Deep knowledge of data modeling, data warehousing (e.g., Snowflake, Redshift, BigQuery), and cloud-native databases. - Experience working with cloud platforms (AWS, GCP, Azure) and managed data services. - Experience with orchestration and workflow tools like Apache Airflow, Luigi, or Prefect. - Strong understanding of data governance, lineage, cataloging, and security practices. - Ability to le