Remote Senior Data Engineer

Summary

The job is for a Data Platform Engineer who will design and build resilient data pipelines, architect data infrastructure, collaborate with various teams, and lead a team. The role requires extensive experience with Azure data services, strong programming skills, knowledge of data modeling, Agile development methods, and certifications on Azure Data Engineering.

Requirements

• 7+ years of data engineering experience leading implementations of large-scale lakehouses on Databricks, Snowflake, or Synapse
• 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
• 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
• 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

Responsibilities

• 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