<p><p><b>Key Responsibilities : </b><br/><br/></p>Data Product Development : Development of data products such as data warehouses, data lakes, and databases to enhance the capabilities of the Data & Analytics teams.<br/><br/><p>Technical Leadership : Guide the technical direction for data engineering initiatives, ensuring adherence to best practices in design, implementation, and optimization.</p><br/><br/><p>Cross- functional Collaboration : Partner closely with teams across the organization to understand their data needs and design solutions that deliver impactful business outcomes.</p><br/><br/><p>Pipeline Optimization & Troubleshooting : Identify and address inefficiencies in data pipelines, optimizing for cost and performance.
Troubleshoot and resolve complex issues in the data engineering & CI/CD : Design, develop, and maintain automated data pipelines and CI/CD processes to enable seamless deployment of new features and fixes.</p><br/><b>Skills & Qualifications : </b><br/><br/><b>Experience : </b><br/><br/>- 4+ years of experience in data engineering, particularly in cloud environments and big data technologies.<br/><br/><p>- Proven experience in designing and building scalable, high- performance data architectures, with familiarity with open- source tools and frameworks.</p><br/><b>Technical Skills : </b><br/><br/>SQL Expertise : Proficient in SQL (preferably MySQL) for querying, managing databases, handling complex queries, and optimising performance.<br/><br/><p>Programming Proficiency : Strong programming skills, particularly with Python.</p><br/><br/><p>Data Pipeline & Architecture : Solid experience in designing and managing data warehouses, data pipelines (ETL/ELT), and data modelling.</p><br/><br/><p>Cloud Platforms (AWS) : Hands- on experience with AWS services such as EC2, S3, Lambda, Athena, Kinesis, Redshift, Glue, EMR, DynamoDB, IAM, KMS, Step Functions, SQS, SNS, and CloudWatch.</p><br/><br/><p>Real- time & Batch Data Processing : Experience building and maintaining data pipelines for both real- time and batch processing using tools like Spark, Flink, or Kafka.</p><br/><br/><p>Version Control : Expertise with Git, GitLab, or GitHub for managing code and collaboration.</p><br/><b>Soft Skills : </b><br/><br/>- Strong analytical and logical thinking with excellent communication skills to collaborate effectively with cross- functional teams.<br/><br/><p>- Ability to manage multiple priorities while consistently delivering high- quality results on time.</p><br/><br/><p>- Adaptability to changing technologies and requirements in a fast- paced work environment.</p><p></p><br/><br/></p> (ref:hirist.tech)