We are a [mention industry/sector] company that thrives on the power of data to drive our decisions and build cutting-edge solutions. We are seeking a highly skilled and experienced Senior Data Engineer with a strong focus on AWS to join our dynamic team in Hyderabad. In this on-site role, you will be instrumental in designing, building, and maintaining our scalable data infrastructure on AWS, enabling data-driven insights and powering our innovative products and Design, develop, and maintain robust and scalable data pipelines using AWS services and industry best practices.
Build and optimize ETL (Extract, Transform, Load) processes to ingest, cleanse, transform, and load data from various sources into our data warehouse and data lake on AWS.
Design and implement efficient data models for our data warehouse and analytical platforms, ensuring data integrity, performance, and usability.
Develop and manage our data warehousing solutions on AWS (e.g., Redshift, Snowflake on AWS), ensuring optimal performance and scalability.
Implement and utilize data analytics tools and services on AWS (e.g., Athena, EMR, SageMaker) to enable data exploration, analysis, and reporting.
Collaborate closely with data scientists, analysts, and other stakeholders to understand their data requirements and provide them with reliable and high-quality data.
Implement data quality checks and monitoring to ensure data accuracy and consistency.
Optimize data pipelines and queries for performance and efficiency.
Implement and maintain data security and governance policies on the AWS data platform.
Stay up-to-date with the latest AWS data services and technologies.
Troubleshoot and resolve data-related issues in a timely manner.
Contribute to the documentation of data pipelines, data models, and ETL processes.
Mentor and guide junior data engineers on the Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
Proven work experience as a Data Engineer, with significant experience in building and maintaining data infrastructure on AWS.
Strong understanding of Data Engineering principles and best practices.
Expertise in Data Modeling techniques for both relational and dimensional models.
Deep understanding and hands-on experience with ETL processes and tools, including design, development, and optimization.
Solid experience in designing and managing Data Warehousing solutions, preferably on AWS (e.g., Redshift).
Proficiency in Data Analytics concepts and tools on AWS (e.g., Athena, S3, Glue, EMR, SageMaker).
Strong proficiency in working with AWS data services and tools (e.g., S3, EC2, RDS, Redshift, Glue, Lambda, IAM, CloudWatch).
Excellent knowledge of SQL and experience with various database systems.
Strong problem-solving and analytical skills with the ability to troubleshoot complex data issues.
Experience in developing and maintaining robust and scalable data pipelines.
Excellent communication and collaboration skills.
Bonus Points
Experience with big data technologies like Hadoop, Spark, or Kafka.
Familiarity with data visualization tools (e.g., Tableau, Power BI).
Experience with scripting languages like Python for data manipulation and automation.
Knowledge of data governance and security best practices in the cloud.
AWS certifications (e.g., AWS Certified Data Engineer Associate).
(ref:hirist.tech)
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