Enterprise Data Engineer

About the Role : We are seeking an experienced and highly motivated Enterprise Data Engineer to join our Data & Analytics team. In this role, you will be responsible for designing, developing, and maintaining robust data pipelines, architectures, and integrations that enable scalable and secure enterprise data solutions. You will collaborate closely with data scientists, analysts, software engineers, and business stakeholders to drive data-centric decision-making across the organization. Key Responsibilities : - Design and implement scalable and resilient ETL/ELT pipelines to ingest, transform, and integrate data from various structured and unstructured sources. - Build and optimize data lake, data warehouse, and data mesh architectures to support enterprise-level analytics and reporting needs. - Develop and manage data integration solutions across cloud platforms, on-premise systems, APIs, and third-party tools. - Ensure data quality, integrity, governance, and security through automated validation, lineage tracking, and metadata management. - Collaborate with data architects and DevOps engineers to deploy and monitor data solutions in CI/CD environments. - Participate in the evaluation and selection of modern data tools, platforms, and practices to enhance data engineering processes. - Partner with business and analytics teams to understand requirements and translate them into technical specifications. - Document data flow processes, architecture diagrams, and system interfaces. - Support data migration, modernization, and cloud transformation initiatives. Technical Skills & Tools : Data Engineering & Integration : - ETL/ELT Tools : Apache Airflow, Azure Data Factory, Informatica, Talend, dbt - Data Modeling : Dimensional modeling, Star/Snowflake schemas, Data Vault - Big Data Ecosystems : Hadoop, Spark, Kafka, Hive, Presto Cloud Platforms : - Azure : Azure Synapse, Azure Data Lake, Azure Databricks, Azure Functions - AWS : Redshift, Glue, S3, Lambda - GCP : BigQuery, Cloud Dataflow, Pub/Sub Databases : - Relational : SQL Server, PostgreSQL, Oracle, MySQL - NoSQL : MongoDB, Cassandra, Cosmos DB Programming Languages : - Proficient in : Python, SQL, PySpark Nice to have : Scala, Java, Shell scripting DevOps & CI/CD : - Git, GitHub/GitLab, Azure DevOps, Jenkins - Containerization : Docker, Kubernetes - Infrastructure as Code : Terraform, ARM templates Data Governance & Security : - Data cataloging tools (e.g., Azure Purview, Alation, Collibra) - Role-based access control (RBAC), data masking, encryption Monitoring & Logging : - Prometheus, Grafana, ELK stack, Azure Monitor, Datadog Qualifications : - Bachelors or Masters degree in Computer Science, Information Systems, or related field. - 4 years of experience as a Data Engineer or in a similar role. - Proven track record of building scalable data architectures in enterprise environments. - Strong understanding of data lifecycle management and best practices in data engineering. - Excellent problem-solving, communication, and collaboration skills. Nice to Have : - Experience with real-time data streaming and event-driven architectures. - Exposure to machine learning pipelines and ML Ops tools. - Certifications in Azure, AWS, or Google Cloud (ref:hirist.tech)

Location: pune, IN

Posted Date: 4/18/2025