Data Platform Lead

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Summary of the Position: Work closely with data engineering teams, source data application teams and product owners to design, implement and support the data platform capabilities and analytics solutions that provide insights to make better decisions. Implement data platform, data migration and data engineering solutions using Azure products and services: (Azure Data Lake Storage, Azure Data Factory, Azure Functions, Azure Databricks, Unity Catalog, etc.). Perform multiple aspects involved in the development lifecycle – design, cloud engineering (Infrastructure, network, security, and administration), ingestion, preparation, data modeling, testing, CICD pipelines, performance tuning, deployments, consumption, BI, observability, alerting, production support. Collaborate within a team environment as well as work independently. Be a part of a DevOps team that completely owns and supports their product. Implement batch, streaming and CDC data pipelines using cloud technologies. Defines, promotes and enforces coding standards, engineering best practices and privacy and security guidelines across the platform. 

Main Responsibilities:

• Architectural ownership of data movement techniques including replication (CDC), messaging, and near real time data transfer.
• Deep understanding of backend infrastructure and how platform services are built on top of it.
• Knowledge of security approaches and tools for data storage, movement and access, including data catalog and access governance (Unity Catalog, Purview).
• Perform Data Acquisition requirements/information gathering and design cost-effective, reusable data acquisition patterns and ingestion accelerators.
• Provides guidance regarding the use of data engineering tools, capability of tools to deliver information, and subject matter expertise regarding current systems and emerging technology.
• Lead governance and enforcement of data pipeline patterns and standards — including pipeline scaffolding, shared libraries, CI/CD policies and deployment gates.
• Analyze and recommend changes to increase productivity level of developers in working environment, treating friction removal for engineering teams as a platform deliverable.
• Understanding user needs as well as understanding the technical requirements and limitations when building platform services.
• Managing cross dependencies across teams to ensure alignment, as well as adjusting team directions when gaps exist.
• Aligning with the strategy vision for various platform components and related services to increase adoption and deliver business results.
• Defines and promotes best practices and design principles for data engineering pipelines development techniques and platform architecture independently and in partnership with other members of the data team - leadership.
• Develops and proposes options with pros/cons and risk, and works with stakeholders to finalize the best solution that meets business needs.
• Establishes credibility with partners while managing expectations. Ensures frequent, continuous and effective communications with team members, within IT, and with stakeholders to set expectations and negotiate priorities appropriately, via both formal and informal channels / mechanisms.
• Understand the underlying technologies and applications utilized within specified area of responsibility to direct how to design, develop, test, and implement requirements.
• Mentors and coaches engineers on platform standards and best practices, acting as the technical reference for the data platform.

Minimum Qualifications

• Completed Bachelor's Degree
• Advanced/Fluent Level of English
• Progressive experience in software solution development using agile, DevOps, operating in a product model that includes designing, developing, and implementing large-scale applications or data engineering solutions·
• Progressive experience of cloud development and data lake experience (prefer Microsoft Azure) including Azure Data Factory, Azure Databricks, Azure DevOps, Azure Blob Storage, Azure Data Lake and Azure Functions, CI/CD: GitHub, Azure DevOps, Bicep scripting.
• Experience in ADLS, Databricks (Unity Catalog, Delta Live Tables, Asset Bundles), ADF, Purview
• Demonstrated experience defining platform standards, reusable frameworks or shared libraries consumed by multiple engineering teams
• Strong SQL skills