4+ Amazon Redshift Jobs in Chennai | Amazon Redshift Job openings in Chennai

Technical Skills:

• Ability to understand and translate business requirements into design.
• Proficient in AWS infrastructure components such as S3, IAM, VPC, EC2, and Redshift.
• Experience in creating ETL jobs using Python/PySpark.
• Proficiency in creating AWS Lambda functions for event-based jobs.
• Knowledge of automating ETL processes using AWS Step Functions.
• Competence in building data warehouses and loading data into them.

Responsibilities:

• Understand business requirements and translate them into design.
• Assess AWS infrastructure needs for development work.
• Develop ETL jobs using Python/PySpark to meet requirements.
• Implement AWS Lambda for event-based tasks.
• Automate ETL processes using AWS Step Functions.
• Build data warehouses and manage data loading.
• Engage with customers and stakeholders to articulate the benefits of proposed solutions and frameworks.

Role Summary

As a Data Engineer, you will be an integral part of our Data Engineering team supporting an event-driven server less data engineering pipeline on AWS cloud, responsible for assisting in the end-to-end analysis, development & maintenance of data pipelines and systems (DataOps). You will work closely with fellow data engineers & production support to ensure the availability and reliability of data for analytics and business intelligence purposes.

Requirements:

·      Around 4 years of working experience in data warehousing / BI system.

·      Strong hands-on experience with Snowflake AND strong programming skills in Python

·      Strong hands-on SQL skills

·      Knowledge with any of the cloud databases such as Snowflake,Redshift,Google BigQuery,RDS,etc.

·      Knowledge on debt for cloud databases

·      AWS Services such as SNS, SQS, ECS, Docker, Kinesis & Lambda functions

·      Solid understanding of ETL processes, and data warehousing concepts

·      Familiarity with version control systems (e.g., Git/bit bucket, etc.) and collaborative development practices in an agile framework

·      Experience with scrum methodologies

·      Infrastructure build tools such as CFT / Terraform is a plus.

·      Knowledge on Denodo, data cataloguing tools & data quality mechanisms is a plus.

·      Strong team player with good communication skills.

Overview Optisol Business Solutions

OptiSol was named on this year's Best Companies to Work for list by Great place to work. We are a team of about 500+ Agile employees with a development center in India and global offices in the US, UK (United Kingdom), Australia, Ireland, Sweden, and Dubai. 16+ years of joyful journey and we have built about 500+ digital solutions. We have 200+ happy and satisfied clients across 24 countries.

Benefits, working with Optisol

·      Great Learning & Development program

·      Flextime, Work-at-Home & Hybrid Options

·      A knowledgeable, high-achieving, experienced & fun team.

·      Spot Awards & Recognition.

·      The chance to be a part of next success story.

·      A competitive base salary.

More Than Just a Job, We Offer an Opportunity To Grow. Are you the one, who looks out to Build your Future & Build your Dream? We have the Job for you, to make your dream comes true.

Data Engineer- Senior

Cubera is a data company revolutionizing big data analytics and Adtech through data share value principles wherein the users entrust their data to us. We refine the art of understanding, processing, extracting, and evaluating the data that is entrusted to us. We are a gateway for brands to increase their lead efficiency as the world moves towards web3.

What are you going to do?

Design & Develop high performance and scalable solutions that meet the needs of our customers.

Closely work with the Product Management, Architects and cross functional teams.

Build and deploy large-scale systems in Java/Python.

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Create data tools for analytics and data scientist team members that assist them in building and optimizing their algorithms.

Follow best practices that can be adopted in Bigdata stack.

Use your engineering experience and technical skills to drive the features and mentor the engineers.

What are we looking for ( Competencies) :

Bachelor’s degree in computer science, computer engineering, or related technical discipline.

Overall 5 to 8 years of programming experience in Java, Python including object-oriented design.

Data handling frameworks: Should have a working knowledge of one or more data handling frameworks like- Hive, Spark, Storm, Flink, Beam, Airflow, Nifi etc.

Data Infrastructure: Should have experience in building, deploying and maintaining applications on popular cloud infrastructure like AWS, GCP etc.

Data Store: Must have expertise in one of general-purpose No-SQL data stores like Elasticsearch, MongoDB, Redis, RedShift, etc.

Strong sense of ownership, focus on quality, responsiveness, efficiency, and innovation.

Ability to work with distributed teams in a collaborative and productive manner.

Benefits:

Competitive Salary Packages and benefits.

Collaborative, lively and an upbeat work environment with young professionals.

Job Category: Development

Job Type: Full Time

Job Location: Bangalore

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.