ZS
Our most valuable asset is our people
ZS
What You'll Do:
- Build, Orchestrate and optimize data pipelines to extract, transform, and load (ETL) data from various sources into the organization's data warehouse or data lake.
- Integrate data from diverse sources such as databases, APIs, streaming platforms, and file systems into cohesive data pipelines
- Implement data integration solutions that support real-time, batch, and incremental data processing.
- Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data.
- Develop and maintain high-performance data pipelines that seamlessly integrate data from various sources into data warehouses, data lakes, and other storage solutions.
- Develop monitoring and alerting mechanisms to identify and address data quality issues proactively.
- Optimize ETL (Extract, Transform, Load) processes for efficiency, reliability, and data quality.
- Implement and manage data storage solutions, including relational databases, NoSQL databases, and distributed file systems.
- Manage the infrastructure and resources required to support data engineering workflows, including compute clusters, storage systems, and data processing frameworks.
- Implement security controls and data governance measures for an application to protect sensitive data and ensure compliance with regulatory requirements such as GDPR, CCPA, HIPAA, and PCI-DSS. Implement encryption, access controls, and auditing mechanisms to safeguard data privacy and integrity.
- Write production-ready, testable code that adheres to engineering best practices and accounts for edge cases and error handling.
- Develop comprehensive unit tests and integration tests to validate data pipeline functionality and data integrity.
- Stay up to date with the latest data engineering tools, technologies, and methodologies, and evaluate their applicability to the team's needs.
- Collaborate with business analysts, and other stakeholders to understand data requirements and translate them into robust engineering solutions.
- Work closely with other engineering teams to integrate data solutions seamlessly into the overall technology ecosystem.
- Participate actively in agile ceremonies, communicate progress, and manage dependencies effectively.
What You'll Bring:
- 1-3 years of experience in a data engineering role, with a focus on building scalable, reliable, and high-performance data systems.
- A relevant bachelor's or master's degree in computer science, Data Engineering, or a related technical field
- Proficiency in programming language - Java.
- Extensive experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud-based data platforms (e.g., AWS, Azure).
- Exposure to Gen AI tools and models
- Strong experience with core Java API's
- Expertise in data integration and ETL tools (e.g., Talend, Informatica, Apache NiFi).
- Proven track record of designing and implementing data pipelines, data storage solutions, and data processing workflows.
- Hands-on experience with distributed computing frameworks and cloud-based data services.
- Demonstrated ability to collaborate with cross-functional teams and communicate technical solutions effectively.
- Ability to travel to other client offices or locations as needed.
- Strong communications skills.
Additional Skills:
- Strong understanding of data warehousing, and data lake concepts and best practices.
- Familiarity with CI/CD pipelines and application monitoring practices.
- Certifications in data engineering (e.g., Azure Data Engineer, AWS Certified Data Engineer) are a plus.
Perks \& Benefits:
Travel:
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