Data Integration Engineer

Job Summary

We seek a Senior Data Engineer to design and optimize scalable data pipelines and processing solutions using Big Data, cloud, and AI technologies. Collaborate with architects, data scientists, and engineers to deliver high-performance, production-ready data systems.

Responsibilities

• Design, develop, and maintain scalable batch and real-time data pipelines using Apache Spark/PySpark, SQL, and Python to support large-scale data processing

• Develop and optimize ETL/ELT pipelines to ensure efficient data ingestion and transformation

• Build data ingestion frameworks integrating databases, APIs, files, and streaming platforms for reliable data flow

• Utilize AWS services including S3, Glue, EMR, Redshift, Kinesis, Lambda, and DynamoDB to deploy and manage cloud-based data solutions

• Develop and optimize data processing workflows using Hadoop, Hive, Spark, Kafka, Cloudera, and Databricks for high throughput and low latency

• Perform SQL and Spark performance tuning to enhance processing speed and resource utilization

• Design and implement data models, data warehouses, and data lake architectures to support analytics and reporting needs

• Develop CI/CD pipelines and manage containerized deployments using Docker, Kubernetes, and OpenShift to streamline development and operations

• Integrate Generative AI and NLP capabilities into enterprise data applications to enhance data insights and automation

• Develop solutions leveraging LLM frameworks, RAG, vector databases, and AI APIs to support advanced AI-driven data applications

• Collaborate with solution architects, data scientists, software engineers, and business stakeholders to deliver scalable, production-ready data solutions

• Participate in system design, development, testing, deployment, and provide production support to ensure system reliability and performance

Required competencies and certifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or related field

• Minimum 8 years of experience in Data Engineering / Big Data with expertise in large-scale data processing

• Proficient programming skills in Python, Java, and/or Scala

• Hands-on experience with Apache Spark/PySpark, SQL, Hadoop, and Hive

• Experience working with AWS cloud platform and its data services

• Knowledge of data warehouses, relational databases, and data lake technologies

• Experience with Kafka, Airflow, Jenkins, Git, and CI/CD practices