Lead Data Engineer

atlascopcogroup

Pune 8 Years Exp Posted 11h ago

Data Modelling & Design: Expertise in data modelling techniques, including relational (SQL) and non-relational (NoSQL) databases.
Data Warehousing & ETL: Solid understanding of data warehousing concepts, ETL (Extract, Transform, Load) processes, and big data technologies.
Programming Languages: Proficiency in SQL and potentially scripting languages like Python, Spark, etc. for data manipulation and automation.
Cloud Platforms: Knowledge of cloud platforms (Microsoft Azure, Data Bricks, Fabric) for deploying and managing data solutions.
Data Management & Security: Understanding of data governance, security best practices, and data access controls.
Certifications: good to have relavent certifications which shows academic regor e.g., Microsoft Certified: Azure Solutions Architect Expert, Databricks Certified Solution Architect

To succeed, you will need

Communication & Collaboration: Excellent communication skills to bridge the gap between technical and non-technical stakeholders.
Problem-Solving & Critical Thinking: Ability to analyze complex data problems and design effective solutions.
Project Management: Experience managing data-related projects and ensuring successful execution.
Teamwork: Ability to guide & collaborate effectively with data engineers, analysts, data scientists, and business teams.
Strategic thinking and Enterprise-level solution design

You can discuss with stakeholders about their requirements and clearly communicate back your understanding of the requirements.
You can work with the stakeholders to understand the big picture and work towards it.
Work with team members and other users from the organization at different levels for performance improvement and suggestions.

Communication skills, Facilitation: Excellent communication skills to bridge the gap between technical and non-technical stakeholders (business users, data engineers, analysts, data scientists).
Collaboration: Ability to work effectively in a team environment, fostering collaboration and knowledge sharing across the data team.
Analytical Thinking: Strong ability to analyse complex business needs and translate them into technical solutions for data analytics projects.
Technical Architecture Design: Skilled at designing and implementing scalable data pipelines, platforms, and tools to support data analytics at an enterprise level.
- Technology Selection: Deep knowledge of various data technologies (cloud platforms, data lakes, data warehouses, analytics tools) to recommend the best fit for specific needs.