Data & Analytics Consultant (Databricks / Azure)

Appstronauts is hiring for a Data & Analytics Consultant role focused on modern Azure Data Platform technologies, working on long-term projects with experienced technical and business teams. The position involves collaboration with business stakeholders and analysts to design data models and build data pipelines supporting decision-making.

• Strong experience with Databricks.
• Strong experience with Apache Spark (PySpark).
• Advanced SQL skills.
• Experience with Microsoft Azure.
• Experience with Azure Data Factory (ADF).
• Strong knowledge of ETL/ELT design and implementation.
• Experience with batch and near real-time data processing.
• Knowledge of Delta Lake (MERGE operations, versioning, optimization).
• Understanding of Lakehouse architecture.
• Experience with Unity Catalog and access management.
• Experience with Power BI.
• Understanding of Data Governance and Data Quality principles.
• Strong analytical thinking and problem-solving skills.
• Ability to understand business processes and data dependencies.
• Experience defining KPIs and analytical metrics with business stakeholders.
• Ability to translate business language into data models and technical solutions.
• Experience conducting business workshops.
• Strong requirements gathering and clarification skills.
• Ability to identify gaps and inconsistencies in requirements.
• Experience working in agile and changing environments.
• Strong communication and stakeholder management skills.

Nice to have:

• Experience in enterprise-scale Azure environments.
• Experience in regulated industries such as energy, finance, healthcare, or telecommunications.
• Experience working with executive stakeholders.

• Collaborate with business stakeholders to understand analytical needs and define data requirements.
• Lead workshops and discovery sessions with business users.
• Translate business requirements into data models, ETL/ELT processes, and technical specifications.
• Design and develop scalable data pipelines using Databricks, PySpark, Azure, and SQL.
• Build and optimize batch and near real-time data processing solutions.
• Design and maintain Lakehouse architectures.
• Implement and manage Delta Lake solutions.
• Define and maintain KPIs, metrics, and analytical datasets.
• Support data governance, data quality, and access management initiatives.
• Create source-to-target mappings and data documentation.
• Identify data quality issues and propose corrective actions.
• Partner with business teams to explain technical constraints and opportunities.