Job Description & Scope
Job description Responsibilities: Design and architect enterprise-scale data platforms, integrating diverse data sources and tools Develop real-time and batch data pipelines to support analytics and machine learning Define and enforce data governance strategies to ensure security, integrity, and compliance along with optimizing data pipelines for high performance, scalability, and cost efficiency in cloud environments Implement solutions for real-time streaming data (Kafka, AWS Kinesis, Apache Flink) and adopt DevOps/DataOps best practices Required Skills: Strong experience in designing scalable, distributed data systems and programming (Python, Scala, Java) with expertise in Apache Spark, Hadoop, Flink, Kafka, and cloud platforms (AWS, Azure, GCP) Proficient in data modeling, governance, warehousing (Snowflake, Redshift, Big Query), and security/compliance standards (GDPR, HIPAA) Hands-on experience with CI/CD (Terraform, Cloud Formation, Airflow, Kubernetes) and data infrastructure optimization (Prometheus, Grafana) Nice to Have: Experience with graph databases, machine learning pipeline integration, real-time analytics, and IoT solutions Contributions to open-source data engineering communities Role: Data Platform Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Doctorate: Doctorate Not Required Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Architecture AirflowBig QueryAzureApache FlinkHadoopKafkaCloud FormationPrometheusFlinkGrafanaRedshiftApache SparkTerraformGCPSnowflakemachine learning pipeline integrationAWSAWS KinesisKubernetes
