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Data Engineer

3 months ago

Raleigh, United States Crescens Full time

Job Title: Data Engineer - Azure Platform

Location: Raleigh,NC(Onsite)

Duration: 3+ Months

Note:

Inperson interview

Responsibilities:

We are looking for an experienced Data Engineer to join our team. You will use various methods to import raw data into Azure Cloud. You will analyze data and create rules for the ETL process. The import process will also include identifying the business rules and apply them to the files stored in staging area before moving the files to processed area.

The ideal candidate will have a strong background in data engineering, along with expertise in cloud computing. This role offers an exciting opportunity to play a key role in modernizing our technology stack and driving our organization's digital

transformation journey.

Responsibilities:

Collaborate with cross-functional business teams to understand requirements,

analyze, and organize raw data import by identifying the ETL rules.

Identify and apply transformation rules for legacy data migration from mainframe

systems to the Azure cloud platform.

Develop and implement data pipelines, ETL processes, and data integration

solutions to facilitate the conversion of data.

Develop and maintain documentation, best practices, and standards for data

engineering processes and procedures.

Provide technical leadership and mentorship to team members, guiding them in best

practices for data engineering and cloud migration projects.

Explore ways to enhance data quality and reliability.

Requirements and Skills

1.Data Modeling and Database Design:

- Proficiency in designing and implementing relational and non-relational

databases.

- Knowledge of data modeling techniques and tools.

2. Azure Data Services:

- Deep understanding and hands-on experience with Azure data services such as

Azure SQL Database, Azure Cosmos DB, Azure Data Lake Storage, Azure Blob

Storage, etc.

3. ETL (Extract, Transform, Load) Processes:

- Expertise in designing and implementing ETL processes using tools like Azure

Data Factory or Azure Databricks.

- Knowledge of data integration and transformation techniques.

4. SQL and T-SQL:

- Proficient in writing complex SQL queries and stored procedures.

- Familiarity with Transact-SQL (T-SQL) for managing and querying SQL Serverdatabases.

5. Data Security and Compliance:

- Knowledge of data security best practices and experience implementing security

measures for data storage and processing on Azure.

- Awareness of compliance requirements and ability to implement solutions that

adhere to NC DPI and DIT regulations.

6. Data Monitoring and Optimization:

- Ability to set up monitoring and logging for data pipelines and databases.

- Skills in optimizing data storage and processing for performance and costeffectiveness.

7. Scripting and Automation:

- Proficiency in scripting languages like Python or PowerShell for automating data

engineering tasks.

-Knowledge of Azure Resource Manager (ARM) templates for infrastructure as code.

Additionally, obtaining relevant certifications, such as the Microsoft Certified: Azure

Data Engineer Associate, can further validate and enhance these skills.

Qualifications:

Bachelor's degree in computer science, Engineering, or a related field

Proven experience as a data engineer, with a strong focus on data migration, ETL,

and data integration.

Hands-on experience with data warehousing concepts, database technologies (SQL

on Azure)

Strong problem-solving skills, attention to detail, and the ability to work effectively in

a fast-paced environment.

Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholder s.

Required Skills:

Proficiency in designing and implementing relational and nonrelational databases.

Knowledge of data modeling

techniques and tools.

Hands-on experience with Azure

data services such as Azure SQL

Database, Azure Cosmos DB,

Azure Data Lake Storage, Azure

Blob Storage, etc.

Expertise in designing and

implementing ETL processes

using tools like Azure Data

Factory or Azure Databricks.

Knowledge of data integration

and transformation techniques.

Proficient in writing complex SQL

queries and stored procedures

Knowledge of data security best

practices and experience

implementing security measures

for data storage and processing

on Azure.

Ability to set up monitoring and

logging for data pipelines and

databases.

Skills in optimizing data storage

and processing for performance

and cost-effectiveness

Proficiency in scripting languages

like Python or PowerShell for

automating data engineering

tasks

Knowledge of Azure Resource

Manager (ARM) templates for

infrastructure as code