Data Platform Expert developing and maintaining data solutions for analysis and reporting at Magna Electronics. Collaborating with various teams to enhance data - driven decision making and insights.
About the role
- Data Engineer joining Contour Software's development team to handle various big data projects. Focus on cloud data lake architecture and machine learning implementation.
Responsibilities
- Write efficient queries to extract and analyze large datasets while ensuring seamless systems integration by developing robust data workflows.
- Design, develop, and maintain scalable ETL solutions for data pipelines, enhancing and optimizing existing processes to meet evolving business needs.
- Develop and expand the organization’s data technology stack to support advanced data processing and analytics needs, leveraging tools like AWS MapReduce and PySpark for big data handling.
- Apply machine learning techniques to clean and process data, supporting future initiatives to integrate machine learning into analytics workflows.
- Continuously evaluate and adopt the most efficient tools and technologies for data extraction, transformation, analysis, and integration.
- Build a strong understanding of customer business needs to deliver tailored and impactful data solutions, collaborating with stakeholders to translate business requirements into technical implementations.
- Utilize AWS services, including MapReduce and related tools, to enable scalable data processing and pipeline optimization while ensuring security, scalability, and cost-efficiency.
- Monitor and improve the performance of data systems and processes, staying updated on industry trends and emerging technologies in data engineering and analytics.
Requirements
- Minimum 3 years of experience with AWS cloud data lake architectures including services like S3, Glue, Athena, and Redshift.
- Hands on experience with Apache Airflow for designing and managing complex data workflows.
- Deep understanding of data warehouse concepts, architectures, and structures.
- Expertise in cloud technologies, particularly AWS services, including AWS Glue, AWS Data Lake, and Amazon EMR for big data processing.
- Proven ability to design and build robust, scalable data pipelines for big data processing and transformation.
- Hands-on experience with big data tools and frameworks such as PySpark, Databricks, and related technologies.
- Proficiency in programming languages such as Python for data manipulation, transformation, and analysis.
- Advanced Python development skills, including experience with AWS SDKs (e.g. boto3) for interacting with cloud services.
- Proficiency in Apache Kafka for real-time data streaming and event-driven architectures.
- Strong SQL skills with a focus on complex query development and optimization.
- Familiarity with NoSQL databases such as DynamoDB or MongoDB.
- Experience integrating Python applications with RESTful APIs and external services.
- Deep understanding of data security best practices, including encryption at rest and in transit.
- Hands-on experience in implementing AWS KMS (Key Management Services) for managing encryption keys.
- Familiarity with IAM policies, VPC configurations, and security groups for securing data pipelines.
- Familiarity with machine learning concepts and their application to data cleaning and integration tasks.
- Advanced English proficiency, with excellent communication skills for collaborating with stakeholders.
Benefits
- Market-leading Salary
- Medical Coverage – Self & Dependents
- Parents Medical Coverage
- Provident Fund
- Employee Performance-based bonuses
- Home Internet Subsidy
- Conveyance Allowance
- Profit Sharing Plan [Tenured Employees Only]
- Life Benefit
- Child Care Facility
- Company Provided Lunch/Dinner
- Professional Development Budget
- Recreational area for in-house games
- Sporadic On-shore training opportunities
- Friendly work environment
- Leave Encashment
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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