Job Description Senior Data Engineer

Job Title Senior Data Engineer

- Total Experience: 5+ Years
- Relevant Experience: 3+ Years

Qualification

- Bachelors Degree (Graduate) in Computer Science, Information Technology, Engineering, or related field.

Work Location

- Trivandrum / Kochi / Remote

Shift

- General Shift with overlapping US working hours.

Joining

- Immediate

Mandatory Skills

- AWS EMR
- Apache Spark
- PostgreSQL
- DynamoDB
- Apache Iceberg

Primary Skills

- AWS EMR
- Apache Spark
- PostgreSQL
- DynamoDB
- Apache Iceberg

Good to Have Skills

- Python Programming
- Apache Spark Programming

Job Summary

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.

Required Technical Skills 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

Required Experience
- 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
- 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.

Preferred Qualifications

Experience with additional AWS services including:

- Amazon Kinesis
- Amazon Kinesis Firehose
- Amazon SQS
- Amazon Bedrock
- Amazon SageMaker

Additional preferred skills:

- 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 recent 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 improvemen

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior AWS Data Engineer (Uttar Pradesh)
🏢 Sparix Global
📍 Uttar Pradesh