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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
5-7 years of experience in Data Engineering with solid experience in design, development and implementation of end-to-end data ingestion and data processing system in AWS platform.
2-3 years of experience in AWS Glue, Lambda, Appflow, EventBridge, Python, PySpark, Lake House, S3, Redshift, Postgres, API Gateway, CloudFormation, Kinesis, Athena, KMS, IAM.
Experience in modern data architecture, Lake House, Enterprise Data Lake, Data Warehouse, API interfaces, solution patterns, standards and optimizing data ingestion.
Experience in build of data pipelines from source systems like SAP Concur, Veeva Vault, Azure Cost, various social media platforms or similar source systems.
Expertise in analyzing source data and designing a robust and scalable data ingestion framework and pipelines adhering to client Enterprise Data Architecture guidelines.
Proficient in design and development of solutions for real-time (or near real time) stream data processing as well as batch processing on the AWS platform.
Work closely with business analysts, data architects, data engineers, and data analysts to ensure that the data ingestion solutions meet the needs of the business.
Troubleshoot and provide support for issues related to data quality and data ingestion solutions. This may involve debugging data pipeline processes, optimizing queries, or troubleshooting application performance issues.
Experience in working in Agile/Scrum methodologies, CI/CD tools and practices, coding standards, code reviews, source management (GITHUB), JIRA, JIRA Xray and Confluence.
Experience or exposure to design and development using Full Stack tools.
Strong analytical and problem-solving skills, excellent communication (written and oral), and interpersonal skills.
Bachelor's or master's degree in computer science or related field.
- Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
- Good understanding of the underlying business and workings of cross functional teams for successful execution
- Design and develop analyses based on business requirement needs and challenges.
- Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
- Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
- Identify and use appropriate investigative and analytical technologies to interpret and verify results.
- Apply and learn a wide variety of tools and languages to achieve results
- Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.
Requirements
- 2 - 4 years of relevant experience in Data science.
- Preferred education: Bachelor's degree in a technical field or equivalent experience.
- Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
- Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
- Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
- Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
- Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
- Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
- Experience in risk and credit score domains preferred.
THE IDEAL CANDIDATE WILL
- Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
- Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
- Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
- Work hands-on across various MLOps problems and provide thought leadership
- Grow and manage large teams with diverse skillsets
- Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists
ELIGIBILITY CRITERIA
- BE/BTech/MTech (Specialization/courses in ML/DS)
- At-least 7+ years of Consulting services delivery experience
- Very strong problem-solving skills & work ethics
- Possesses strong analytical/logical thinking, storyboarding and executive communication skills
- 5+ years of experience in Python/R, SQL
- 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
- Hands on work experience in DevOps
- Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
- Exposure on cloud technologies like Azure, AWS or GCP
- Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
- Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
- Experience with one or more Container-ecosystem (Docker, Kubernetes)
- Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
- Good understanding of OOP & Data Structures concepts
Nice to Have:
- Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
- Experience in Helm is a plus
- Strong understanding of data infrastructure, data warehouse, or data engineering
You can expect to –
- Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
- Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
- Work in a diverse environment that keeps evolving
- Hone your entrepreneurial skills as you contribute to growth of the organization
at Virtusa
- Minimum 1 years of relevant experience, in PySpark (mandatory)
- Hands on experience in development, test, deploy, maintain and improving data integration pipeline in AWS cloud environment is added plus
- Ability to play lead role and independently manage 3-5 member of Pyspark development team
- EMR ,Python and PYspark mandate.
- Knowledge and awareness working with AWS Cloud technologies like Apache Spark, , Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS
- Analyze and organize raw data
- Build data systems and pipelines
- Evaluate business needs and objectives
- Interpret trends and patterns
- Conduct complex data analysis and report on results
- Build algorithms and prototypes
- Combine raw information from different sources
- Explore ways to enhance data quality and reliability
- Identify opportunities for data acquisition
- Should have experience in Python, Django Micro Service Senior developer with Financial Services/Investment Banking background.
- Develop analytical tools and programs
- Collaborate with data scientists and architects on several projects
- Should have 5+ years of experience as a data engineer or in a similar role
- Technical expertise with data models, data mining, and segmentation techniques
- Should have experience programming languages such as Python
- Hands-on experience with SQL database design
- Great numerical and analytical skills
- Degree in Computer Science, IT, or similar field; a Master’s is a plus
- Data engineering certification (e.g. IBM Certified Data Engineer) is a plus
Company Description
At Bungee Tech, we help retailers and brands meet customers everywhere and, on every occasion, they are in. We believe that accurate, high-quality data matched with compelling market insights empowers retailers and brands to keep their customers at the center of all innovation and value they are delivering.
We provide a clear and complete omnichannel picture of their competitive landscape to retailers and brands. We collect billions of data points every day and multiple times in a day from publicly available sources. Using high-quality extraction, we uncover detailed information on products or services, which we automatically match, and then proactively track for price, promotion, and availability. Plus, anything we do not match helps to identify a new assortment opportunity.
Empowered with this unrivalled intelligence, we unlock compelling analytics and insights that once blended with verified partner data from trusted sources such as Nielsen, paints a complete, consolidated picture of the competitive landscape.
We are looking for a Big Data Engineer who will work on the collecting, storing, processing, and analyzing of huge sets of data. The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them.
You will also be responsible for integrating them with the architecture used in the company.
We're working on the future. If you are seeking an environment where you can drive innovation, If you want to apply state-of-the-art software technologies to solve real world problems, If you want the satisfaction of providing visible benefit to end-users in an iterative fast paced environment, this is your opportunity.
Responsibilities
As an experienced member of the team, in this role, you will:
- Contribute to evolving the technical direction of analytical Systems and play a critical role their design and development
- You will research, design and code, troubleshoot and support. What you create is also what you own.
- Develop the next generation of automation tools for monitoring and measuring data quality, with associated user interfaces.
- Be able to broaden your technical skills and work in an environment that thrives on creativity, efficient execution, and product innovation.
BASIC QUALIFICATIONS
- Bachelor’s degree or higher in an analytical area such as Computer Science, Physics, Mathematics, Statistics, Engineering or similar.
- 5+ years relevant professional experience in Data Engineering and Business Intelligence
- 5+ years in with Advanced SQL (analytical functions), ETL, Data Warehousing.
- Strong knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures, data modeling and performance tuning.
- Ability to effectively communicate with both business and technical teams.
- Excellent coding skills in Java, Python, C++, or equivalent object-oriented programming language
- Understanding of relational and non-relational databases and basic SQL
- Proficiency with at least one of these scripting languages: Perl / Python / Ruby / shell script
PREFERRED QUALIFICATIONS
- Experience with building data pipelines from application databases.
- Experience with AWS services - S3, Redshift, Spectrum, EMR, Glue, Athena, ELK etc.
- Experience working with Data Lakes.
- Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space
- Sharp problem solving skills and ability to resolve ambiguous requirements
- Experience on working with Big Data
- Knowledge and experience on working with Hive and the Hadoop ecosystem
- Knowledge of Spark
- Experience working with Data Science teams
- Should have good hands-on experience in Informatica MDM Customer 360, Data Integration(ETL) using PowerCenter, Data Quality.
- Must have strong skills in Data Analysis, Data Mapping for ETL processes, and Data Modeling.
- Experience with the SIF framework including real-time integration
- Should have experience in building C360 Insights using Informatica
- Should have good experience in creating performant design using Mapplets, Mappings, Workflows for Data Quality(cleansing), ETL.
- Should have experience in building different data warehouse architecture like Enterprise,
- Federated, and Multi-Tier architecture.
- Should have experience in configuring Informatica Data Director in reference to the Data
- Governance of users, IT Managers, and Data Stewards.
- Should have good knowledge in developing complex PL/SQL queries.
- Should have working experience on UNIX and shell scripting to run the Informatica workflows and to control the ETL flow.
- Should know about Informatica Server installation and knowledge on the Administration console.
- Working experience with Developer with Administration is added knowledge.
- Working experience in Amazon Web Services (AWS) is an added advantage. Particularly on AWS S3, Data pipeline, Lambda, Kinesis, DynamoDB, and EMR.
- Should be responsible for the creation of automated BI solutions, including requirements, design,development, testing, and deployment