Data Engineer
4 weeks ago
Experience - 6+Years
Primary Skills - ADF, SQL Server, Databricks NoteBooks, Data Pipelines, SPROCs, Data Warehouse, Databricks DataLake
Secondary Skills - PowerBl, Data modeling
Notice Period - Immediate - 15 days
Job Description: The Data Engineer is responsible for designing, developing, and maintaining data pipelines and data warehouses to support the organization‘s data-driven decision-making processes. The Data Engineer will work closely with data scientists, analysts, and other stakeholders to ensure the quality, efficiency, and reliability of data processing and storage systems. Key
Responsibilities:
Design, develop, and maintain data pipelines to ingest, transform, and load data from various sources into the organization‘s data warehouse and data lake.
Implement and manage data integration processes using ADF, SQL Server, and Databricks Notebooks.
Develop and optimize stored procedures (SPROCs) for efficient data processing and retrieval.
Design and implement data models, schemas, and data structures for the data warehouse and data lake.
Collaborate with data scientists and analysts to ensure data quality, integrity, and consistency.
Monitor and maintain data pipeline performance, identifying and resolving bottlenecks and inefficiencies.
Implement and manage data security, access controls, and compliance measures.
Provide technical support and troubleshooting for data pipeline and data warehouse issues.
Stay up-to-date with industry trends, best practices, and emerging technologies in data engineering and data management.
Mentor and support junior team members in data engineering principles and practices.
Qualifications:
Bachelor‘s degree in Computer Science, Data Science, Engineering, or a related field.
6+ years of experience in data engineering, data warehousing, or data management.
Strong proficiency in ADF, SQL Server, and Databricks Notebooks.
Experience with data pipeline design and implementation, including ETL processes.
Knowledge of data modeling, schema design, and data structure optimization.
Familiarity with data warehousing and data lake concepts and best practices.
Strong understanding of data quality, integrity, and consistency principles.
Experience with stored procedures (SPROCs) and SQL Server.
Strong problem-solving and troubleshooting skills.
Excellent communication and collaboration skills.
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