Delivery Lead-Data Engineer

Acuity Analytics; Gurugram District; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

Acuity Analytics is seeking a Senior Data Engineer to design and maintain scalable data platforms using Azure Databricks, PySpark, and Python. You will build data pipelines, oversee data infrastructure, and lead end-to-end delivery from planning to deployment.

The role requires strong SQL skills, API development with FastAPI, and familiarity with DevOps practices. Experience in financial services data is a plus, and collaboration with stakeholders is essential.

Qualifications

• 5-7 years of experience in software development with a focus on data projects.
• Proven experience as a Data Engineer with experience in Azure cloud.
• Experience implementing solutions using Azure cloud services (ADF, Lake Gen2, Databases, Data Fabric).
• Strong SQL skills with RDMS or NoSQL databases.
• Experience developing APIs using FastAPI or similar frameworks in Python.
• Familiarity with the DevOps lifecycle (git, Jenkins) and CI/CD processes.
• Good understanding of ETL/ELT processes.
• Experience in financial services data is a plus.
• Assist stakeholders with data-related issues and data governance.

Responsibilities

• Design, construct, and maintain scalable data management systems using Azure Databricks.
• Oversee data infrastructure workflows and data pipelines.
• Lead planning, estimation, implementation, monitoring, and tracking of data modules.
• Develop and maintain data pipeline documentation and data governance artifacts.
• Review and optimize PySpark/Python code for performance improvements.

Skills

Python

PySpark

SQL

FastAPI

Data modeling

Data governance

Stakeholder comms

Problem solving

Tools

Azure Databricks

Azure Data Factory

Azure Lake Gen 2

Azure Databases

Azure Data Fabric

API Gateway

Azure Functions

Git

Jenkins

Job description

Job Description:

The Data Engineer will design, construct, and maintain scalable data management systems using Azure Databricks. This role involves supervising the upkeep of existing data infrastructure workflows and creating data processing pipelines utilizing Databricks Notebooks, Spark SQL, Python, and other Databricks tools. The Senior Data Engineer will oversee and lead the module through planning, estimation, implementation, monitoring, and tracking.

Key Responsibilities

• 5-7 years of experience in software development with a focus on data projects using Python, PySpark, and associated frameworks.


• Proven experience as a Data Engineer with experience in Azure cloud.


• Experience implementing solutions using Azure cloud services, Azure Data Factory, Azure Lake Gen 2, Azure Databases, Azure Data Fabric, API Gateway management, Azure Functions.


• Strong SQL skills with RDMS or NoSQL databases.


• Experience with developing APIs using FastAPI or similar frameworks in Python.


• Familiarity with the DevOps lifecycle (git, Jenkins, etc.), CI/CD processes.


• Good understanding of ETL/ELT processes.


• Experience in the financial services industry, financial instruments, asset classes, and market data are a plus.


• Assist stakeholders with data-related technical issues and support their data infrastructure needs.


• Develop and maintain documentation for data pipeline architecture, development processes, and data governance.


• In-depth knowledge of data warehousing concepts, architecture, and implementation.


• Extremely strong organizational and analytical skills with strong attention to detail.


• Strong track record of excellent results delivered to internal and external clients.


• Excellent problem-solving skills, with the ability to work independently or as part of a team.


• Strong communication and interpersonal skills, with the ability to effectively engage with both technical and non-technical stakeholders.

• Able to work independently without the need for close supervision and collaboratively as part of cross-team efforts.

Key competencies

• Interpret business requirements and work with internal resources as well as application vendors.


• Design, develop, and maintain Data Bricks solutions and relevant data quality rules.


• Troubleshoot and resolve data-related issues.


• Configure and create data models and data quality rules to meet customer needs.


• Handle multiple database platforms like Microsoft SQL Server and Oracle.


• Review and analyze data from multiple internal and external sources.


• Analyze existing PySpark/Python code and identify areas for optimization.


• Write new optimized SQL queries or Python scripts to improve performance and reduce run time.


• Identify opportunities for efficiency and innovative approaches to completing the scope of work.


• Write clean, efficient, and well-documented code that adheres to best practices and Council IT coding standards.


• Maintain and operate existing custom code processes.


• Participate in team problem-solving efforts and offer ideas to solve client issues.


• Query writing skills with the ability to understand and implement changes to SQL functions and stored procedures.


• Effectively communicate with business and technology partners, peers, and stakeholders. Deliver results under demanding timelines to real-world business problems.


• Work independently and multi-task effectively.


• Configure system settings and options and execute unit/integration testing.


• Develop end-user release notes, training materials, and deliver training to a broad user base.


• Identify and communicate areas for improvement.


• Responsible for quality checks and adhering to the agreed Service Level Agreement (SLA) / Turn Around Time (TAT).

Requirements: