Data Engineer

Ashley Global Capability Center; Chennai; On-site; INR 7,005,253 - 10,507,880; Full time

Job summary

Join a forward-thinking company that is at the forefront of data engineering and warehousing. This role offers an exciting opportunity to lead the full development cycle, from architecture to implementation, while collaborating with various teams to optimize data processes. You will leverage cutting-edge technologies and mentor team members, ensuring quality and efficiency throughout the development lifecycle. If you have a passion for data and a desire to innovate, this is the perfect opportunity to make a significant impact in the industry.

Qualifications

• 5+ years of experience in data engineering or related fields.
• Advanced skills in data warehouse architectures and dimensional models.
• Proficient in programming languages like Spark, Python, and SQL.

Responsibilities

• Responsible for the full development cycle of Data Engineering concepts.
• Ensure data quality and consistency; implement automation opportunities.
• Collaborate with teams to build robust data pipelines and environments.

Skills

Data Engineering

Data Warehousing

Spark

Python

SQL

Azure Services

Big Data Technologies

API / RESTful Services

Education

Bachelor's Degree in Computer Science

Technical MS (preferred)

Tools

Azure Synapse Analytics

Power BI

Docker

Kubernetes

Job description

Get AI-powered advice on this job and more exclusive features.

1. Responsible for the full development cycle of Data Engineering & Warehousing concepts, including requirements gathering, architecture, design, implementation, and maintenance.
2. Identify and resolve data issues to ensure data quality and consistency; determine and implement automation opportunities.
3. Continuously develop expertise in data and data models within the data warehouse and support business domains.
4. Communicate effectively, both orally and in writing, with technical personnel, business managers, and senior leadership regarding data inquiries and requests.
5. Conduct and facilitate internal testing & user acceptance testing.
6. Develop technical specifications and design documents.
7. Ensure quality processes are followed throughout all phases of the Development Lifecycle.
8. Design and implement efficient and effective functional design solutions.
9. Collaborate with the Business and Business Intelligence teams to meet requirements.
10. Build robust data pipelines and integrate with multiple components and data sources.
11. Build and maintain scalable and secure data environments.
12. Design and architect new product features, promote cutting-edge technologies, and mentor team members in adopting these technologies.
13. Collaborate with the Data Science team on complex machine learning models to optimize data processing, structure, and accessibility for model performance.
14. Apply domain technical expertise to provide solutions to the business and its operations.

Required Qualifications

1. Bachelor's Degree in computer science, Information Technology, Management Information Systems, or a related field. Technical MS preferred.
2. At least 5 years of professional experience in data engineering/data warehousing or related fields.
3. Advanced skills with data warehouse architectures, dimensional models, star schema designs, and in-memory/columnar databases.
4. Proficient in programming languages such as Spark, Spark SQL, R, Python, Java, and Scala.
5. Knowledge of Delta Lake.
6. Proficient in SQL Server syntax, Microsoft/Azure services like Data Factory, Azure Analysis Services (Tabular), and familiarity with DAX and MDX syntaxes.
7. Experience with Microsoft Azure Cloud services for design, management, monitoring, security, and privacy of data.
8. Strong experience with Database Management Systems, including SQL and NoSQL.
9. Experience working with Azure Synapse Analytics and Azure Blob Storage.
10. Experience with API / RESTful data services.
11. Proficient with big data technologies such as Spark, Databricks, Hadoop, Hive, etc.
12. Knowledge of data discovery, analytics, and BI tools like Power BI.
13. Knowledge of containerization techniques such as Docker and Kubernetes.

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Information Technology

Industries: Software Development