Data Engineer/Analytics Engineer (AI)

Data Analytics Engineer

Key Responsibilities

• Design, develop, and maintain data pipelines and ETL processes with a core focus on data transformation, utilising SQL, Python, and DBT. Develop complex SQL queries to extract, transform, and load data, with a strong emphasis on transforming data for analytical purposes, including aggregations, cleansing, and data modeling.
• Utilise Python to automate data transformation tasks, implement custom transformation logic, and enhance data pipeline functionality.
• Implement data transformations and build data pipelines using DBT, with a focus on creating reusable and maintainable transformation models.
• Assemble scalable and reusable data sets that meet business requirements.
• Develop and maintain data transformation logic to prepare data for analysis and reporting.
• Create and maintain data storage solutions. Ensure the accuracy, consistency, and completeness of data through data validation, testing, and documentation.
• Collaborate with stakeholders to understand their data needs and provide support.
• Troubleshoot and resolve data-related technical issues.
• Explore ways to enhance data quality and reliability. Write technical documentation as required.
• Conform to information security policies and report any security incidents or improvements. Ensure data is compliant with relevant policies and regulations (PII, GDPR etc.).

Skills and Experience

• Hands-on experience with Google Cloud Platform
• Deep working knowledge of databases like Google BigQuery.
• Hands-on experience with SQL database design and writing SQL queries.
• Experience in designing and implementing data flows/pipelines and transformations.
• Technical expertise with data models, data mining, and segmentation techniques.
• Great numerical and analytical skills.
• Attention to detail and ability to critically evaluate information.
• Proven problem-solving skills with the ability to form well-thought-out conclusions and recommendations.
• Strong stakeholder engagement skills with a proven track record of managing multiple stakeholders.
• Ability to self-manage workload and prioritise according to demands and timelines.
• Excellent verbal and written communication skills.
• Ability to work effectively in a team environment

Sr. Data Engineer

What a typical day at work would look like

• Collaborate with stakeholders: Engage in discussions with business users, BI analysts, data engineers to understand their data needs and translate them into technical solutions.
• Design and implement data pipelines: Architect and build data pipelines using GCP services like Cloud Dataflow, Cloud Dataproc, and BigQuery to ensure efficient data ingestion, transformation, and delivery.
• Develop data models: Design and implement data models in BigQuery, considering performance, scalability, and security requirements.
• Manage and optimize data storage: Manage data storage on Google Cloud Storage, optimizing for cost-efficiency and performance.
• Ensure data quality: Implement data validation and quality checks throughout the datapipeline to ensure data accuracy and integrity.
• Troubleshoot and resolve issues: Diagnose and solve complex data-related issues, ensuring smooth data flow and optimal performance.
• Stay updated on GCP advancements: Keep abreast of the latest Google Cloud Platform offerings and best practices to continually enhance our data solutions.

Your Key Knowledge Areas shall be:

• Deep understanding of GCP data services: Expertise in using GCP services such as Cloud Dataflow, Cloud Dataproc, BigQuery, Cloud Storage, Data Catalog, and Data Fusion.
• Datamodeling and architecture: Proven experience designing and implementing data models, including dimensional modeling and data warehousing principles.
• Data warehousing and data lakes: Strong understanding of data warehousing concepts, data lake architectures, and best practices for data management.
• Data pipeline development: Proficiency in building data pipelines using tools like Apache Beam, Apache Spark, or other relevant technologies.
• SQL and Python programming: Strong command of SQL for data querying and manipulation,and proficiency in Python for data analysis and automation.
• Data governance and security: Understanding of data governance principles, data security best practices, and compliance requirements.

What do you bring with you

5+ years of experience as a Data Engineer/Data Architect or similar role:

Proven track record of designing and implementing data solutions on Google Cloud Platform

• Strong analytical and problem-solving skills: Ability to analyze complex data challenges and provide innovative solutions.
• Excellent communication and collaboration skills: Proven ability to effectively communicate technical concepts to both technical and non-technical audiences.
• Passion for data and technology: A genuine interest in data, its potential, and the latest advancements in data technology.
• Continuous learner: A proactive and enthusiastic approach to learning new technologies and techniques.

If Interested to apply

Email : kollapudi.bhagyanandu@randstadusa.com

Ph: 8019969609

Whatsapp 7661074661

Join us in walk-in drive Thursday, Friday

From 1.30 PM

Contact Person - Nandu

Location - Raheja Mindspace

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