We are looking for an experienced Java Spark AWS Data Engineer with strong hands-on expertise in Java, Apache Spark, AWS, SQL, and large-scale data processing.
The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and distributed data-processing applications on AWS. The role requires strong software engineering fundamentals along with practical experience in Spark performance optimization, cloud-native data services, ETL/ELT pipelines, and production support.
Candidates must have 8+ years of overall experience, with strong hands-on expertise in Java, Apache Spark, AWS, and large-scale data engineering solutions.
- Design and develop scalable data-processing applications using Java and Apache Spark.
- Build and maintain production-grade ETL/ELT data pipelines on AWS.
- Develop distributed batch and real-time data-processing solutions.
- Process large volumes of structured, semi-structured, and unstructured data.
- Build Spark applications using Java, Spark SQL, and DataFrame APIs.
- Optimize Spark jobs for performance, memory utilization, partitioning, and scalability.
- Design and manage data ingestion and transformation workflows using AWS services.
- Work with AWS services such as Amazon S3, EMR, Glue, Lambda, Athena, Redshift, RDS, and CloudWatch.
- Develop and integrate REST APIs and backend services using Java where required.
- Implement data validation, reconciliation, quality checks, and error-handling mechanisms.
- Design scalable data models and data warehouse solutions.
- Troubleshoot Spark jobs, data pipeline failures, and production performance issues.
- Implement monitoring, logging, and alerting for data-processing workloads.
- Participate in system design, architecture discussions, and code reviews.
- Write unit, integration, and data-pipeline tests.
- Support CI/CD pipelines and automated deployments.
- Collaborate with Data Engineers, Architects, DevOps/SRE teams, and business stakeholders.
- Perform root-cause analysis and implement permanent fixes for production issues.
RequirementsRequired Skills – Comma-Separated
Java, Java 8, Java 11, Java 17, Apache Spark, Spark SQL, Spark DataFrames, Distributed Data Processing, ETL, ELT, Data Engineering, Data Pipelines, Data Ingestion, Data Transformation, Data Validation, Data Quality, SQL, AWS, Amazon S3, Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, AWS Lambda, Amazon RDS, AWS CloudWatch, AWS IAM, Batch Processing, Data Warehousing, Data Modeling, Parquet, JSON, CSV, Spark Optimization, Performance Tuning, Partitioning, Broadcast Joins, Caching, Git, Maven, Gradle, CI/CD, Linux, Production Support, Troubleshooting, Root Cause Analysis
Skills Required
- 8+ years of overall professional experience
- Strong hands-on expertise with Java, including Java 8, 11, or 17
- Strong hands-on expertise with Apache Spark, Spark SQL, and DataFrame APIs
- Experience building distributed data-processing applications and large-scale data engineering solutions
- Experience developing ETL/ELT pipelines, data ingestion, transformation, validation, and quality workflows
- Experience with AWS services including S3, EMR, Glue, Athena, Redshift, Lambda, RDS, CloudWatch, and IAM
- Experience with SQL, data warehousing, data modeling, Parquet, JSON, and CSV
- Experience with Spark optimization, performance tuning, partitioning, broadcast joins, and caching
- Experience with Git, Maven or Gradle, CI/CD, and Linux
- Experience with production support, troubleshooting, root-cause analysis, monitoring, logging, and alerting
- Experience developing REST APIs and Java backend services
- Experience writing unit, integration, and data-pipeline tests
What We Do
Synthlane Technologies is a deep-tech software company that develops scalable, secure digital solutions for startups, enterprises, and government organizations. Its services include custom software development, consulting, application modernization, AI and machine-learning solutions, cybersecurity and digital forensics, ERP implementation, and managed applications. The company focuses on helping organizations integrate systems, improve workflows, modernize technology, protect digital assets, and achieve measurable business growth.
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