Senior Data Engineer - Data Modeling & Warehousing (7-12 yrs)

Job Description :

We are looking for a Data Engineer to join our team with growing requirement of data & analytics. The hire will be responsible for building and optimizing our data storage and pipeline architecture to provide a strong base for our Sales Platform, Data Consumers, and Data Analysts/Scientists on a vast range of projects.

The ideal candidate is an experienced software developer who enjoys optimizing data systems and building them from the ground up.

They must be self-directed and comfortable supporting the data needs of multiple systems / projects.

The candidate will contribute to our division's data strategy and implementation of analytics & data-science platform to support our next generation of data & analytics initiatives.

Responsibilities :

- Build and optimize data pipeline to consume data from various source, transform & model it, and then distribute it to multiple consumers.

- Identify, design, and implement improvements / automations for optimizing data processing, storage, and availability, while maintaining scalability, etc.

- Create / maintain data access tools for analytics / data scientist team members allowing them to consume data efficiently & continuously.

- Build and support analytics tools that utilize the data pipeline to provide actionable insights into data trends and other key business metrics.

- Manage our data storage and processing systems across on-premises and cloud.

- Develop and support data pipeline orchestration, and analytics & machine learning projects.

- Support migration of the data platform from on-premises to cloud infrastructure.

- Work with various stakeholders including the Senior Management, Technology and Client teams to assist with data & analytics related projects and issues.

Qualification :

- We are looking for a candidate with 7+ years of experience in a Data Engineer role, who has attained a bachelor's or master's degree in computer science, information technology/systems or another relevant technical field.

- Advanced working knowledge and experience with data modelling, data warehousing concepts, database design principles, query authoring (SQL) and performance optimization.

- A successful history of manipulating, processing, and extracting value from large, disconnected datasets.

- Knowledge of data integration, migration, and synchronization techniques in distributed environments.

- Hands-on programming experience with Python, Java, or C#.

- Excellent problem-solving and analytical skills with attention to details.

- Strong project management and organizational skills.

- Experience supporting and working with cross-functional teams in a dynamic environment.

- Excellent communication and collaboration skills.

Skillset and Experience :

- Experience with Relational database systems like Sybase, SQL Server, Postgres, etc.

- Experience with object-oriented or function scripting languages : Python (NumPy, Pandas), Java, C++, or Scala, etc.

- Experience with Cloud technologies like Microsoft Azure, Databricks, Snowflake, etc.

- Experience with data-science tools / workbench like Dataiku, Jupyter, Rapid Miner, etc. is a plus.

- Experience with Big Data tools / technologies : Hadoop, Pig, Hive, Hue, PySpark etc. is a plus.

- Experience with ETL tools like Azure Data Factory, Informatica, etc. is a plus.

- Working knowledge of integrating visualization tools like Tableau, QlikView, Power BI etc. is a major plus.

- Experience with machine learning / artificial intelligence techniques like regression, classification, clustering, time series, text mining, large language model, etc. is a plus.