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 Preferred competencies and qualifications Experience with Docker, Kubernetes, or OpenShift container orchestration platforms Familiarity with Databricks, Snowflake, and Cloudera platforms Exposure to Generative AI, LLMs, RAG, LangChain/LangGraph, and vector databases Strong analytical, problem-solving, and communication skills