– Big Data Engineer
Big Data Engineer
We are looking for a skilled Big Data Engineer with strong experience in Scala PySpark AWS Glue Databricks Delta Lake and Amazon EMR to design develop and optimize scalable data engineering solutions.
should have hands-on experience in big data pipeline development data validation and profiling data quality frameworks performance optimization and Snowflake migration. The candidate will work on high-volume data processing cloud-based data platforms migration initiatives and building reliable data pipelines using modern Big Data technologies.
Design develop and maintain scalable Big Data pipelines using Scala PySpark AWS Glue and Databricks. Develop robust ETL/ELT pipelines for structured semi-structured and large-volume datasets. Work with Apache Spark/PySpark for distributed data processing and transformation. Develop and optimize data processing solutions using Delta Lake and Parquet. Build and manage data pipelines using AWS Glue and Amazon EMR. Perform data validation profiling reconciliation and quality checks across data pipelines. Implement and maintain Data Quality Frameworks to ensure data accuracy completeness consistency and reliability. Participate in Snowflake migration projects including data extraction transformation loading validation and reconciliation. Optimize Spark jobs SQL queries data transformations partitioning caching and resource utilization for improved performance. Troubleshoot production data pipelines and resolve data quality performance and processing issues. Implement appropriate error handling logging monitoring and recovery mechanisms within data pipelines. Work with Delta Lake features such as ACID transactions schema evolution partitioning and optimization. Utilize AI Coding Assistants to improve development productivity code quality debugging documentation and testing. Collaborate with data architects analysts application teams and cloud engineers to deliver end-to-end data solutions. Follow best practices for coding version control CI/CD security and data governance. Required Technical SkillsBig Data & Programming Strong hands-on experience with Scala and PySpark. Strong understanding of Apache Spark architecture and distributed data processing. Experience developing enterprise-grade Big Data pipelines. Strong SQL skills for data transformation and validation. AWS & Cloud Hands-on experience with AWS Glue. Experience with Amazon EMR and Spark-based workloads. Good understanding of AWS data services and cloud-based data engineering architectures. Databricks & Delta Lake Strong experience with Databricks. Hands-on experience with Delta Lake Delta tables partitioning schema evolution and optimization. Understanding of Spark performance tuning within Databricks environments. Data Engineering & Formats Experience with Parquet and other distributed data storage formats. Experience in ETL/ELT pipeline development. Strong understanding of data warehousing and data lake concepts. Experience with data validation and data profiling. Data Quality Experience implementing Data Quality Frameworks. Knowledge of data completeness accuracy consistency uniqueness and reconciliation checks. Ability to identify and troubleshoot data anomalies. Snowflake Migration Hands-on experience or strong understanding of Snowflake migration projects. Experience with data migration transformation validation reconciliation and performance optimization. Performance Optimization Experience optimizing Spark jobs and Big Data pipelines. Knowledge of partitioning caching joins shuffle optimization file-size optimization and query tuning. Ability to troubleshoot performance bottlenecks in distributed processing environments. AI Coding Assistants Experience using AI-assisted coding tools such as GitHub Copilot or similar AI coding assistants. Ability to leverage AI tools for code generation refactoring debugging test creation and technical documentation. Good to Have Experience with AWS S3 Lambda Step Functions CloudWatch or related AWS services. Knowledge of Apache Airflow or other workflow orchestration tools. Experience with CI/CD tools such as Git Jenkins GitHub Actions or Azure DevOps. Knowledge of data governance metadata management and data security. Experience working in Agile/Scrum environments. Exposure to Terraform/IaC and cloud automation. Experience with production support and monitoring of large-scale data platforms.
Strong problem-solving and analytical skills. Excellent understanding of distributed data processing. Ability to work with large and complex datasets. Strong debugging and performance-tuning capabilities. Good communication and collaboration skills. Ability to work independently and take ownership of data engineering deliverables. Strong focus on data quality reliability scalability and performance.
Remote
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