[Hiring] Senior Data Engineer @Sparix Global.

Role Description

We are seeking a highly skilled Senior Data Engineer (Contractor) to design, build, and optimize scalable data platforms and pipelines. The ideal candidate will play a critical role in developing modern AWS-based data lakehouse architectures that support advanced analytics and enable data-driven decision-making across the organization. The successful candidate should possess strong expertise in AWS Big Data technologies, distributed data processing, and modern data engineering best practices while collaborating with cross-functional teams to deliver high-quality data solutions.

Key Responsibilities

• Design, develop, and maintain scalable analytical data models and enterprise-grade data platforms.
• Architect, implement, and optimize modern data lakehouse solutions using AWS technologies.
• Build robust, scalable, and high-performance data pipelines using Python, PySpark, Apache Spark, and AWS Glue.
• Develop and optimize ETL/ELT pipelines for structured and semi-structured datasets.
• Ensure high availability, reliability, scalability, and performance of enterprise data systems.
• Design efficient data storage strategies using Apache Iceberg and AWS services.
• Implement data governance, metadata management, and security best practices.
• Collaborate with business stakeholders to translate business requirements into scalable data solutions.
• Partner with architects, DevOps, and operations teams to establish engineering standards and best practices.
• Monitor, troubleshoot, and optimize data workflows for maximum efficiency.
• Perform performance tuning of Spark applications and SQL queries.
• Implement data quality validation, reconciliation, and monitoring processes.
• Build reusable frameworks for data ingestion, transformation, and processing.
• Support cloud migration initiatives and modernization of legacy data platforms.
• Work within Agile/Scrum development environments.
• Ensure compliance with Information Security Management policies and organizational standards.
• Document technical designs, architecture diagrams, and operational procedures.

Qualifications

• Bachelor's Degree (Graduate) in Computer Science, Information Technology, Engineering, or related field.
• 5+ years of professional experience in software development with a strong focus on Data Engineering.
• Minimum 3+ years of hands-on experience with Big Data ecosystems.
• Strong expertise in AWS EMR, Apache Spark, PostgreSQL, DynamoDB, and Apache Iceberg.
• Strong programming skills in Python and Apache Spark.
• Experience building highly scalable, low-latency data systems.
• Experience working with relational and NoSQL databases.
• Proven expertise in designing and implementing AWS-based data lakehouse architectures.
• Hands-on experience with AWS Step Functions, AWS Lambda, and Amazon EventBridge.
• Experience working in Agile software development environments.
• Strong understanding of distributed computing concepts.
• Experience optimizing Spark jobs for performance and scalability.
• Knowledge of data partitioning, indexing, caching, and query optimization techniques.
• Familiarity with cloud-native data engineering practices and CI/CD pipelines.

Requirements

• Big Data Technologies: AWS EMR, Apache Spark, PySpark, Apache Iceberg, AWS Glue.
• Programming Languages: Python, Spark Programming, SQL.
• Databases: PostgreSQL, DynamoDB.
• AWS Cloud Services: AWS EMR, AWS Glue, AWS Lambda, AWS Step Functions, Amazon EventBridge.
• Data Engineering: ETL/ELT Development, Data Lakehouse Architecture, Data Modeling, Data Pipeline Development, Data Warehousing, Data Integration, Data Quality Management.

Preferred Qualifications

• Experience with additional AWS services including: Amazon Kinesis, Amazon Kinesis Firehose, Amazon SQS, Amazon Bedrock, Amazon SageMaker.
• Real-time data streaming architectures.
• Event-driven architecture.
• Machine Learning data pipelines.
• AWS Lake Formation, Amazon Redshift, AWS Aurora.
• Cloud-native data platforms.
• Infrastructure as Code (Terraform/CloudFormation).
• Container technologies (Docker/Kubernetes) are a plus.

Soft Skills

• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal abilities.
• Ability to quickly learn and adapt to new technologies.
• Ability to work independently and collaboratively in cross-functional teams.
• Strong multitasking and time management skills.
• Excellent verbal and written communication skills.
• Strong ownership and accountability.
• Ability to manage multiple priorities in a fast-paced environment.
• Commitment to engineering excellence and continuous improvement.