Lead Azure Data Engineer

Role Name: Data - Tech Lead

Remote - Only W2

Role Description:

As a Data - Tech Lead, you will oversee the technical delivery of data solutions, guiding a team of data engineers and analysts to design, build, and maintain scalable data platforms. You will be responsible for setting technical standards, driving best practices, and ensuring data solutions align with business objectives. This role requires strong leadership, deep technical expertise in data engineering, and the ability to collaborate across teams to deliver high-quality, reliable data products.

Key Responsibilities:

• • Lead the design, development, and maintenance of scalable data platforms and pipelines
  • Set technical standards and best practices for data engineering and analytics
  • Guide and mentor data engineers and analysts, fostering a culture of excellence
  • Collaborate with business stakeholders to translate requirements into technical solutions
  • Ensure data quality, integrity, and security across all data products
  • Oversee performance tuning, optimization, and troubleshooting of data systems
  • Drive adoption of new data technologies and methodologies
  • Develop and maintain technical documentation and knowledge sharing resources
  • Monitor and report on data platform health, usage, and performance
  • Support data governance initiatives and ensure compliance with relevant policies

Required Skills:

• • Proven experience leading data engineering or analytics teams
  • Experienced with the concept of Centralization and De-centralization of Information, establishing Medallion Pattern and Data Mesh Architecture
  • Strong proficiency in data engineering tools and technologies (Databricks, Power BI, SQL, Python, Spark, Hadoop)
  • Expertise in designing and building data pipelines and ETL processes
  • Experience with cloud data platforms (Azure, GCP) and data warehousing solutions (Snowflake, Redshift, BigQuery)
  • Deep understanding of data modeling, data architecture, and database design (relational and NoSQL)
  • Knowledge of data governance, data quality, and security best practices
  • Experience with workflow orchestration tools (Airflow, Luigi)
  • Strong problem-solving and analytical skills
  • Excellent communication, documentation, and stakeholder management abilities
  • Ability to mentor and guide team members in technical and professional development

Nice to Have Experiences/Skills:

• • Experience with machine learning platforms and data science workflows
  • Familiarity with real-time data processing and streaming technologies (Kafka, Flink)
  • Exposure to data visualization and BI tools (Tableau, Power BI)
  • Experience in regulated industries (finance, healthcare)