
3 Days Left Senior Data Engineer
1 day ago
optimize, and maintain data pipelines and architectures. The ideal candidate will have deep
expertise in the Microsoft data engineering ecosystem, particularly leveraging tools such as
Azure Data Factory, Databricks, Alteryx, Synapse Analytics, Microsoft Fabric, and a
strong command of SQL, Python, and Apache Spark.
Key Responsibilities:
Design, develop, and optimize scalable data pipelines and workflows using Azure
Data Factory, Synapse Pipelines, and Microsoft Fabric.
Responsible for transforming and migrating existing Alteryx workflows into scalable
Azure Databricks pipelines, ensuring optimized performance and maintainability.
Collaborate with data engineering and analytics teams to redesign Alteryx pipelines
into Spark-based solutions on Azure Databricks, leveraging Delta Lake and Azure
services for automation and efficiency.
Build and maintain ETL/ELT processes for ingesting structured and unstructured data
from various sources.
Develop and manage data transformation logic using Databricks (PySpark/Spark
SQL) and Python.
Collaborate with data analysts, architects, and business stakeholders to understand
requirements and deliver high-quality data solutions.
Ensure data quality, integrity, and governance across the data lifecycle.
Implement monitoring and alerting for data pipelines to ensure reliability and
performance.
Work with Azure Synapse Analytics to build data models and enable analytics and
reporting.
Utilize SQL for querying and managing large datasets efficiently.
Participate in data architecture discussions and contribute to technical design
decisions.
Required Skills and Qualifications:
3+ years of experience in data engineering or a related field.
Strong experience in Alteryx workflows and data preparation/ETL processes.
Strong proficiency in the Microsoft Azure data ecosystem including:
o Azure Data Factory (ADF)
o Azure Synapse Analytics
o Microsoft Fabric
o Azure Databricks
Solid experience with Python and Apache Spark (including PySpark).
Advanced skills in SQL for data manipulation and transformation.
Experience in designing and implementing data lakes and data warehouses.
Familiarity with data governance, security, and compliance standards.
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Preferred Qualifications:
Microsoft Azure certifications (e.g., Azure Data Engineer Associate).
Experience with DevOps tools and CI/CD practices in data workflows.
Knowledge of REST APIs and integration techniques.
Background in agile methodologies and working in cross-functional teams.
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