Lead Analyst

2 months ago

Chennai, Tamil Nadu, India Sutherland Global Full time

Role : Data Engineer


Role Overview :


We are seeking an experienced and motivated Lead Analytics - Data Engineer to join our dynamic team. The ideal candidate will have a strong background in data engineering, with a focus on SQL, data warehousing, and AWS technologies.


You will be responsible for leading the design, development, and implementation of scalable data solutions that support our analytical and reporting needs. Your expertise in SQL, Python, and AWS services will be critical in optimizing our data infrastructure and enabling data-driven decision-making across the organization.


Key Responsibilities :


1. Data Engineering Leadership :


- Lead the development and maintenance of data pipelines and ETL processes to support data integration, transformation, and loading into data warehouses.


- Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver robust data solutions.


- Provide technical guidance and mentorship to junior data engineers, fostering a culture of continuous learning and improvement.


2. SQL and Data Warehousing :


- Design, implement, and optimize data models and schemas within a data warehouse environment.


- Write complex SQL queries, stored procedures, and functions to support data extraction, transformation, and reporting needs.


- Perform performance tuning and query optimization to ensure efficient data retrieval and processing.


3. AWS Data Services :


- Leverage AWS data services, including Redshift, Lambda, Glue, S3, and others, to build scalable and cost-effective data solutions.


- Implement data storage and processing solutions that align with best practices for security, performance, and cost optimization in the cloud.


- Monitor and maintain the data infrastructure, ensuring high availability, reliability, and security of data assets.


4. Python Scripting and Automation :


- Utilize Python for data manipulation, scripting, and automation tasks to enhance data processing workflows.


- Develop scripts and tools for data quality checks, data validation, and automated reporting.


- Integrate Python-based solutions with AWS services to automate data processing pipelines.


5. Machine Learning and Big Data Technologies (Preferred) :


- Apply knowledge of machine learning concepts and frameworks to support data science initiatives.


- Work with big data technologies such as Spark, Hadoop, or Kafka to process and analyze large-scale datasets.


- Explore opportunities to integrate machine learning models into data pipelines for real-time analytics.


6. Reporting and Visualization :


- Develop and maintain reporting solutions using modern BI tools such as Power BI, Tableau, or SSRS.


- Collaborate with business users to create interactive dashboards and reports that provide actionable insights.


- Ensure data accuracy and consistency across all reporting platforms.


7. DevOps and CI/CD :


- Implement DevOps practices and tools to streamline the deployment and management of data pipelines and infrastructure.


- Set up continuous integration and continuous delivery (CI/CD) pipelines for automated testing, deployment, and monitoring of data solutions.


- Work within agile methodologies such as Scrum or Kanban to deliver high-quality data solutions on time.


8. AWS Certification and Professional Development :


- Maintain and apply knowledge of AWS services through certification as an AWS Certified Developer - Associate, AWS Certified Solutions Architect, or equivalent.


- Stay up-to-date with the latest industry trends, best practices, and emerging technologies in data engineering and cloud computing.


Required Qualifications :


- Bachelor's or Masters degree in Computer Science, Information Technology, or a related field.


- 7+ years of experience in data engineering, with a strong emphasis on SQL, data warehousing, and AWS technologies.


- Proficiency in SQL for complex queries, stored procedures, and performance tuning.


- Hands-on experience with AWS data services (e.g., Redshift, Lambda, Glue, S3).


- Proficiency in Python for data manipulation, scripting, and automation.


- Solid understanding of data warehousing principles and best practices.


- Knowledge of DevOps practices and CI/CD tools.


Preferred Qualifications :


- Experience with machine learning concepts and frameworks.


- Hands-on experience with big data technologies (e.g., Spark, Hadoop, Kafka).


- Experience with modern reporting and visualization tools (e.g., Power BI, Tableau, SSRS).


- Certified AWS Professional (AWS Certified Developer - Associate, AWS Certified Solutions Architect).


- Familiarity with agile methodologies such as Scrum or Kanban.


Personal Attributes :


- Strong analytical and problem-solving skills.


- Excellent communication and collaboration abilities.


- Ability to work independently and lead projects from conception to completion.


- Continuous learner with a passion for staying current with new technologies and best practices.


Why Join Us?


- Opportunity to work with cutting-edge technologies and drive innovation in data engineering.


- Collaborative and inclusive work environment.


- Professional development opportunities, including AWS certification programs.


- Competitive compensation and benefits package.

(ref:hirist.tech)

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