Job
Description
Senior Data Engineer - Azure This is a hands on data platform engineering role that places significant emphasis on consultative data engineering engagements with a wide range of customer stakeholders; Business Owners, Business Analytics, Data Engineering teams, Application Development, End Users and Management teams. You Will: Design and build resilient and efficient data pipelines for batch and real-time streaming Architect and design data infrastructure on cloud using Infrastructure-as-Code tools. Collaborate with product managers, software engineers, data analysts, and data scientists to build scalable and data-driven platforms and tools. Provide technical product expertise, advise on deployment architectures, and handle in-depth technical questions around data infrastructure, PaaS services, design patterns and implementation approaches. Collaborate with enterprise architects, data architects, ETL developers & engineers, data scientists, and information designers to lead the identification and definition of required data structures, formats, pipelines, metadata, and workload orchestration capabilities Address aspects such as data privacy & security, data ingestion & processing, data storage & compute, analytical & operational consumption, data modeling, data virtualization, self-service data preparation & analytics, AI enablement, and API integrations. Lead a team of engineers to deliver impactful results at scale. Execute projects with an Agile mindset. Build software frameworks to solve data problems at scale. Technical Requirements: 7+ years of data engineering experience leading implementations of large-scale lakehouses on Databricks, Snowflake, or Synapse. Prior experience using DBT and PowerBI will be a plus. 3+ years experience architecting solutions for developing data pipelines from structured, unstructured sources for batch and realtime workloads. Extensive experience with Azure data services (Databricks, Synapse, ADF) and related azure infrastructure services like firewall, storage, key vault etc. is required. Strong programming / scripting experience using SQL and python and Spark. Strong Data Modeling, Data lakehouse concepts. Knowledge of software configuration management environments and tools such as JIRA, Git, Jenkins, TFS, Shell, PowerShell, Bitbucket. Experience with Agile development methods in data-oriented projects Other Requirements: Highly motivated self-starter and team player and demonstrated success in prior roles. Track record of success working through technical challenges within enterprise organizations Ability to prioritize deals, training, and initiatives through highly effective time management Excellent problem solving, analytical, presentation, and whiteboarding skills Track record of success dealing with ambiguity (internal and external) and working collaboratively with other departments and organizations to solve challenging problems Strong knowledge of technology and industry trends that affect data analytics decisions for enterprise organizations Certifications on Azure Data Engineering and related technologies.
