28+ Amazon Redshift Jobs in India

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.

About the role:

 Hopscotch is looking for a passionate Data Engineer to join our team. You will work closely with other teams like data analytics, marketing, data science and individual product teams to specify, validate, prototype, scale, and deploy data pipelines features and data architecture.

Here’s what will be expected out of you:

➢ Ability to work in a fast-paced startup mindset. Should be able to manage all aspects of data extraction transfer and load activities.

➢ Develop data pipelines that make data available across platforms.

➢ Should be comfortable in executing ETL (Extract, Transform and Load) processes which include data ingestion, data cleaning and curation into a data warehouse, database, or data platform.

➢ Work on various aspects of the AI/ML ecosystem – data modeling, data and ML pipelines.

➢ Work closely with Devops and senior Architect to come up with scalable system and model architectures for enabling real-time and batch services.

What we want:

➢ 5+ years of experience as a data engineer or data scientist with a focus on data engineering and ETL jobs.

➢ Well versed with the concept of Data warehousing, Data Modelling and/or Data Analysis.

➢ Experience using & building pipelines and performing ETL with industry-standard best practices on Redshift (more than 2+ years).

➢ Ability to troubleshoot and solve performance issues with data ingestion, data processing & query execution on Redshift.

➢ Good understanding of orchestration tools like Airflow.

 ➢ Strong Python and SQL coding skills.

➢ Strong Experience in distributed systems like spark.

➢ Experience with AWS Data and ML Technologies (AWS Glue,MWAA, Data Pipeline,EMR,Athena, Redshift,Lambda etc).

➢ Solid hands on with various data extraction techniques like CDC or Time/batch based and the related tools (Debezium, AWS DMS, Kafka Connect, etc) for near real time and batch data extraction.

Note :

Product based companies, Ecommerce companies is added advantage

Experience: 8+ Years

Work Location: Hyderabad

Mode of work: Work from Office

Senior Data Engineer / Architect

Summary of the Role

The Senior Data Engineer / Architect will be a key role within the data and technology team, responsible for engineering and building data solutions that enable seamless use of data within the organization. 

Core Activities

-         Work closely with the business teams and business analysts to understand and document data usage requirements

-         Develop designs relating to data engineering solutions including data pipelines, ETL, data warehouse, data mart and data lake solutions

-         Develop data designs for reporting and other data use requirements

-         Develop data governance solutions that provide data governance services including data security, data quality, data lineage etc.

-         Lead implementation of data use and data quality solutions

-         Provide operational support for users for the implemented data solutions

-         Support development of solutions that automate reporting and business intelligence requirements

-         Support development of machine learning and AI solution using large scale internal and external datasets

Other activities

-         Work on and manage technology projects as and when required

-         Provide user and technical training on data solutions

Skills and Experience

-         At least 5-8 years of experience in a senior data engineer / architect role

-         Strong experience with AWS based data solutions including AWS Redshift, analytics and data governance solutions

-         Strong experience with industry standard data governance / data quality solutions  

-         Strong experience with managing a Postgres SQL data environment

-         Background as a software developer working in AWS / Python will be beneficial

-         Experience with BI tools like Power BI and Tableau

Strong written and oral communication skills

Description

About us

Welcome to Decision Foundry!

We are both a high growth startup and one of the longest tenured Salesforce Marketing Cloud Implementation Partners in the ecosystem. Forged from a 19-year-old web analytics company, Decision Foundry is the leader in Salesforce intelligence solutions.

We win as an organization through our core tenets. They include:

• One Team. One Theme.
• We sign it. We deliver it.
• Be Accountable and Expect Accountability.
• Raise Your Hand or Be Willing to Extend it

Requirements

• Strong understanding of data management principles and practices (Preferred experience: AWS Redshift).

• Experience with Tableau server administration, including user management and permissions (preferred, not mandatory).

• Ability to monitor alerts and application logs for data processing issues and troubleshooting.

• Ability to handle and monitor support tickets queues and act accordingly based on SLAs and priority.

• Ability to work collaboratively with cross-functional teams, including Data Engineers and BI team.

• Strong analytical and problem-solving skills.

• Familiar with data warehousing concept and ETL processes.

• Experience with SQL, DBT and database technologies such as Redshift, Postgres, MongoDB, etc.

• Familiar with data integration tools such as Fivetran or Funnel.io

• Familiar with programming languages such as Python.

• Familiar with cloud-based data technologies such as AWS.

• Experience with data ingestion and orchestration tools such as AWS Glue.

• Excellent communication and interpersonal skills.

• Should possess experience of 2+ years.

One of our premium-based customers, we are looking to hire a team of Sr. Full Stack Developers in Bangalore, looking for Tech Geeks, who have 5+ years of experience full-time.

PFB the JD:

Responsibilities:

Develop applications conforming to requirement specifications.

Perform code reviews, and unit testing and adhere to and be an advocate of best development practices.

Collaborate with cross-functional teams & squads.

Requirement:

• 5+ years of web development experience using Node.js or similar web technologies.
• Well-versed with front-end code in HTML5, CSS3, Javascript, TypeScript React.js with familiarity in various frameworks and template languages.
• Possess a strong understanding of Functional Programming, especially in JavaScript.
• Proficient with database design, optimization, and tuning in MySQL or MongoDB.
• Experience in design patterns, unit testing, and automation techniques (ex. Playwright).
• Exposure to Amazon Web Services (EC2, S3, EBS, RDS, SQS, Redshift, etc.)
• Exposure to Docker and Kubernetes.
• Exposure to collaborating tools like GitHub, JIRA, and Confluence.
• Experience in frameworks such as Express.js, and NestJs or proven ability to learn on the job.
• Experience in Microservices and REST architecture.
• Exposure to Scrum methodology and XP technical practices such as unit testing, pair programming, test-driven development, continuous integration, or continuous delivery.
• Self-motivated, fast learner, detail-oriented, team player, and a sense of humor.

DATA ENGINEER

Overview

They started with a singular belief - what is beautiful cannot and should not be defined in marketing meetings. It's defined by the regular people like us, our sisters, our next-door neighbours, and the friends we make on the playground and in lecture halls. That's why we stand for people-proving everything we do. From the inception of a product idea to testing the final formulations before launch, our consumers are a part of each and every process. They guide and inspire us by sharing their stories with us. They tell us not only about the product they need and the skincare issues they face but also the tales of their struggles, dreams and triumphs. Skincare goes deeper than skin. It's a form of self-care for many. Wherever someone is on this journey, we want to cheer them on through the products we make, the content we create and the conversations we have. What we wish to build is more than a brand. We want to build a community that grows and glows together - cheering each other on, sharing knowledge, and ensuring people always have access to skincare that really works.

Job Description:

We are seeking a skilled and motivated Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, developing, and maintaining the data infrastructure and systems that enable efficient data collection, storage, processing, and analysis. You will collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to implement data pipelines and ensure the availability, reliability, and scalability of our data platform.

Responsibilities:

Design and implement scalable and robust data pipelines to collect, process, and store data from various sources.

Develop and maintain data warehouse and ETL (Extract, Transform, Load) processes for data integration and transformation.

Optimize and tune the performance of data systems to ensure efficient data processing and analysis.

Collaborate with data scientists and analysts to understand data requirements and implement solutions for data modeling and analysis.

Identify and resolve data quality issues, ensuring data accuracy, consistency, and completeness.

Implement and maintain data governance and security measures to protect sensitive data.

Monitor and troubleshoot data infrastructure, perform root cause analysis, and implement necessary fixes.

Stay up-to-date with emerging technologies and industry trends in data engineering and recommend their adoption when appropriate.

Qualifications:

Bachelor’s or higher degree in Computer Science, Information Systems, or a related field.

Proven experience as a Data Engineer or similar role, working with large-scale data processing and storage systems.

Strong programming skills in languages such as Python, Java, or Scala.

Experience with big data technologies and frameworks like Hadoop, Spark, or Kafka.

Proficiency in SQL and database management systems (e.g., MySQL, PostgreSQL, or Oracle).

Familiarity with cloud platforms like AWS, Azure, or GCP, and their data services (e.g., S3, Redshift, BigQuery).

Solid understanding of data modeling, data warehousing, and ETL principles.

Knowledge of data integration techniques and tools (e.g., Apache Nifi, Talend, or Informatica).

Strong problem-solving and analytical skills, with the ability to handle complex data challenges.

Excellent communication and collaboration skills to work effectively in a team environment.

Preferred Qualifications:

Advanced knowledge of distributed computing and parallel processing.

Experience with real-time data processing and streaming technologies (e.g., Apache Kafka, Apache Flink).

Familiarity with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).

Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).

Experience with data visualization and reporting tools (e.g., Tableau, Power BI).

Certification in relevant technologies or data engineering disciplines.

Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.

Roles & Responsibilities:

Work on implementation of real-time and batch data pipelines for disparate data sources.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
• Build and maintain an analytics layer that utilizes the underlying data to generate dashboards and provide actionable insights.
• Identify improvement areas in the current data system and implement optimizations.
• Work on specific areas of data governance including metadata management and data quality management.
• Participate in discussions with Product Management and Business stakeholders to understand functional requirements and interact with other cross-functional teams as needed to develop, test, and release features.
• Develop Proof-of-Concepts to validate new technology solutions or advancements.
• Work in an Agile Scrum team and help with planning, scoping and creation of technical solutions for the new product capabilities, through to continuous delivery to production.
• Work on building intelligent systems using various AI/ML algorithms. 

Desired Experience/Skill:

• Must have worked on Analytics Applications involving Data Lakes, Data Warehouses and Reporting Implementations.
• Experience with private and public cloud architectures with pros/cons.
• Ability to write robust code in Python and SQL for data processing. Experience in libraries such as Pandas is a must; knowledge of one of the frameworks such as Django or Flask is a plus.
• Experience in implementing data processing pipelines using AWS services: Kinesis, Lambda, Redshift/Snowflake, RDS.
• Knowledge of Kafka, Redis is preferred
• Experience on design and implementation of real-time and batch pipelines. Knowledge of Airflow is preferred.
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

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

Job Title: Data Warehouse/Redshift Admin

Location: Remote

Job Description

AWS Redshift Cluster Planning

AWS Redshift Cluster Maintenance

AWS Redshift Cluster Security

AWS Redshift Cluster monitoring.

Experience managing day to day operations of provisioning, maintaining backups, DR and monitoring of AWS RedShift/RDS clusters

Hands-on experience with Query Tuning in high concurrency environment

Expertise setting up and managing AWS Redshift

AWS certifications Preferred (AWS Certified SysOps Administrator)

Roles and

Responsibilities

Seeking AWS Cloud Engineer /Data Warehouse Developer for our Data CoE team to

help us in configure and develop new AWS environments for our Enterprise Data Lake,

migrate the on-premise traditional workloads to cloud. Must have a sound

understanding of BI best practices, relational structures, dimensional data modelling,

structured query language (SQL) skills, data warehouse and reporting techniques.

 Extensive experience in providing AWS Cloud solutions to various business

use cases.

 Creating star schema data models, performing ETLs and validating results with

business representatives

 Supporting implemented BI solutions by: monitoring and tuning queries and

data loads, addressing user questions concerning data integrity, monitoring

performance and communicating functional and technical issues.

Job Description: -

This position is responsible for the successful delivery of business intelligence

information to the entire organization and is experienced in BI development and

implementations, data architecture and data warehousing.

Requisite Qualification

Essential

-

AWS Certified Database Specialty or -

AWS Certified Data Analytics

Preferred

Any other Data Engineer Certification

Requisite Experience

Essential 4 -7 yrs of experience

Preferred 2+ yrs of experience in ETL & data pipelines

Skills Required

Special Skills Required

 AWS: S3, DMS, Redshift, EC2, VPC, Lambda, Delta Lake, CloudWatch etc.

 Bigdata: Databricks, Spark, Glue and Athena

 Expertise in Lake Formation, Python programming, Spark, Shell scripting

 Minimum Bachelor’s degree with 5+ years of experience in designing, building,

and maintaining AWS data components

 3+ years of experience in data component configuration, related roles and

access setup

 Expertise in Python programming

 Knowledge in all aspects of DevOps (source control, continuous integration,

deployments, etc.)

 Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD

 Hands on ETL development experience, preferably using or SSIS

 SQL Server experience required

 Strong analytical skills to solve and model complex business requirements

 Sound understanding of BI Best Practices/Methodologies, relational structures,

dimensional data modelling, structured query language (SQL) skills, data

warehouse and reporting techniques

Preferred Skills

Required

 Experience working in the SCRUM Environment.

 Experience in Administration (Windows/Unix/Network/Database/Hadoop) is a

plus.

 Experience in SQL Server, SSIS, SSAS, SSRS

 Comfortable with creating data models and visualization using Power BI

 Hands on experience in relational and multi-dimensional data modelling,

including multiple source systems from databases and flat files, and the use of

standard data modelling tools

 Ability to collaborate on a team with infrastructure, BI report development and

business analyst resources, and clearly communicate solutions to both

technical and non-technical team members

• Collaborating across an agile team to continuously design, iterate, and develop big data systems.
• Extracting, transforming, and loading data into internal databases.
• Optimizing our new and existing data pipelines for speed and reliability. 
• Deploying new products and product improvements
• Documenting and managing multiple repositories of code.

• Experience with Pandas to process the data and Jupyter notebooks to keep it all together. 
• Familiar with pulling and pushing files from SFTP and AWS S3.  Familiarity with AWS Athena and Redshift is mandatory. 
• Familiarity with SQL programming to query and transform data from relational Databases. 
• Familiarities with AWS Cloud and Linux (and Linux work environment) are mandatory. 
• Excellent written and verbal communication skills.

• Excellent organizational skills, including attention to precise details. 
• Strong multitasking skills and ability to work in a fast-paced environment  Know your way around REST APIs (Able to integrate not necessary to publish)

• Python 
• Sql
• API 
• AWS 
• GCP 
• OCI 
• Azure 
• Redshift

• 5 years experience in database systems 
• 3 years experience with Python to develop scripts

Company Profile:

Easebuzz is a payment solutions (fintech organisation) company which enables online merchants to accept, process and disburse payments through developer friendly APIs. We are focusing on building plug n play products including the payment infrastructure to solve complete business problems. Definitely a wonderful place where all the actions related to payments, lending, subscription, eKYC is happening at the same time.

We have been consistently profitable and are constantly developing new innovative products, as a result, we are able to grow 4x over the past year alone. We are well capitalised and have recently closed a fundraise of $4M in March, 2021 from prominent VC firms and angel investors. The company is based out of Pune and has a total strength of 180 employees. Easebuzz’s corporate culture is tied into the vision of building a workplace which breeds open communication and minimal bureaucracy. An equal opportunity employer, we welcome and encourage diversity in the workplace. One thing you can be sure of is that you will be surrounded by colleagues who are committed to helping each other grow.

Easebuzz Pvt. Ltd. has its presence in Pune, Bangalore, Gurugram.

Salary: As per company standards.

Designation: Data Engineering

Location: Pune

Experience with ETL, Data Modeling, and Data Architecture

Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties
- Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, Glue.

Experience with AWS cloud data lake for development of real-time or near real-time use cases

Experience with messaging systems such as Kafka/Kinesis for real time data ingestion and processing

Build data pipeline frameworks to automate high-volume and real-time data delivery

Create prototypes and proof-of-concepts for iterative development.

Experience with NoSQL databases, such as DynamoDB, MongoDB etc

Create and maintain optimal data pipeline architecture,

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

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Evangelize a very high standard of quality, reliability and performance for data models and algorithms that can be streamlined into the engineering and sciences workflow

Build and enhance data pipeline architecture by designing and implementing data ingestion solutions.

Employment Type

Full-time

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.