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About Dataweave Pvt Ltd
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Position Overview: We are seeking a talented Data Engineer with expertise in Power BI to join our team. The ideal candidate will be responsible for designing and implementing data pipelines, as well as developing insightful visualizations and reports using Power BI. Additionally, the candidate should have strong skills in Python, data analytics, PySpark, and Databricks. This role requires a blend of technical expertise, analytical thinking, and effective communication skills.
Key Responsibilities:
- Design, develop, and maintain data pipelines and architectures using PySpark and Databricks.
- Implement ETL processes to extract, transform, and load data from various sources into data warehouses or data lakes.
- Collaborate with data analysts and business stakeholders to understand data requirements and translate them into actionable insights.
- Develop interactive dashboards, reports, and visualizations using Power BI to communicate key metrics and trends.
- Optimize and tune data pipelines for performance, scalability, and reliability.
- Monitor and troubleshoot data infrastructure to ensure data quality, integrity, and availability.
- Implement security measures and best practices to protect sensitive data.
- Stay updated with emerging technologies and best practices in data engineering and data visualization.
- Document processes, workflows, and configurations to maintain a comprehensive knowledge base.
Requirements:
- Bachelor’s degree in Computer Science, Engineering, or related field. (Master’s degree preferred)
- Proven experience as a Data Engineer with expertise in Power BI, Python, PySpark, and Databricks.
- Strong proficiency in Power BI, including data modeling, DAX calculations, and creating interactive reports and dashboards.
- Solid understanding of data analytics concepts and techniques.
- Experience working with Big Data technologies such as Hadoop, Spark, or Kafka.
- Proficiency in programming languages such as Python and SQL.
- Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
- Excellent analytical and problem-solving skills with attention to detail.
- Strong communication and collaboration skills to work effectively with cross-functional teams.
- Ability to work independently and manage multiple tasks simultaneously in a fast-paced environment.
Preferred Qualifications:
- Advanced degree in Computer Science, Engineering, or related field.
- Certifications in Power BI or related technologies.
- Experience with data visualization tools other than Power BI (e.g., Tableau, QlikView).
- Knowledge of machine learning concepts and frameworks.
Daily and monthly responsibilities
- Review and coordinate with business application teams on data delivery requirements.
- Develop estimation and proposed delivery schedules in coordination with development team.
- Develop sourcing and data delivery designs.
- Review data model, metadata and delivery criteria for solution.
- Review and coordinate with team on test criteria and performance of testing.
- Contribute to the design, development and completion of project deliverables.
- Complete in-depth data analysis and contribution to strategic efforts
- Complete understanding of how we manage data with focus on improvement of how data is sourced and managed across multiple business areas.
Basic Qualifications
- Bachelor’s degree.
- 5+ years of data analysis working with business data initiatives.
- Knowledge of Structured Query Language (SQL) and use in data access and analysis.
- Proficient in data management including data analytical capability.
- Excellent verbal and written communications also high attention to detail.
- Experience with Python.
- Presentation skills in demonstrating system design and data analysis solutions.
Roles and Responsibilities
- Managing available resources such as hardware, data, and personnel so that deadlines are met.
- Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
- Exploring data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Defining validation framework and establish a process to ensure acceptable data quality criteria are met
- Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
- Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
- Device self-learning strategies through analysis of errors from the models
- Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
- Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
- Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.
Preferred Technical & Professional expertise
- Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
- At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
- In-depth knowledge of cloud analytics tools.
- Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
- Ability to evaluate hardware selection for running ML models for optimal performance
- Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
- Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
- Deep analytical thinking with excellent problem-solving abilities
- Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
- Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
- Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
- Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards
- 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
GCP Data Analyst profile must have below skills sets :
- Knowledge of programming languages like https://apc01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.simplilearn.com%2Ftutorials%2Fsql-tutorial%2Fhow-to-become-sql-developer&data=05%7C01%7Ca_anjali%40hcl.com%7C4ae720b3f3cc45c3e04608da3346b335%7C189de737c93a4f5a8b686f4ca9941912%7C0%7C0%7C637878675987971859%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=EImfaJAD1KHOyrBQ7FkbaPl1STtfnf4QdQlbjw72%2BmE%3D&reserved=0" target="_blank">SQL, Oracle, R, MATLAB, Java and https://apc01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.simplilearn.com%2Fwhy-learn-python-a-guide-to-unlock-your-python-career-article&data=05%7C01%7Ca_anjali%40hcl.com%7C4ae720b3f3cc45c3e04608da3346b335%7C189de737c93a4f5a8b686f4ca9941912%7C0%7C0%7C637878675987971859%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Z2n1Xy%2F3YN6nQqSweU5T7EfUTa1kPAAjbCMTWxDCh%2FY%3D&reserved=0" target="_blank">Python
- Data cleansing, data visualization, data wrangling
- Data modeling , data warehouse concepts
- Adapt to Big data platform like Hadoop, Spark for stream & batch processing
- GCP (Cloud Dataproc, Cloud Dataflow, Cloud Datalab, Cloud Dataprep, BigQuery, Cloud Datastore, Cloud Datafusion, Auto ML etc)
WE ARE GRAPHENE
Graphene is an award-winning AI company, developing customized insights and data solutions for corporate clients. With a focus on healthcare, consumer goods and financial services, our proprietary AI platform is disrupting market research with an approach that allows us to get into the mind of customers to a degree unprecedented in traditional market research.
Graphene was founded by corporate leaders from Microsoft and P&G and works closely with the Singapore Government & universities in creating cutting edge technology. We are gaining traction with many Fortune 500 companies globally.
Graphene has a 6-year track record of delivering financially sustainable growth and is one of the few start-ups which are self-funded, yet profitable and debt free.
We already have a strong bench strength of leaders in place. Now, we are looking to groom more talents for our expansion into the US. Join us and take both our growths to the next level!
WHAT WILL THE ENGINEER-ML DO?
- Primary Purpose: As part of a highly productive and creative AI (NLP) analytics team, optimize algorithms/models for performance and scalability, engineer & implement machine learning algorithms into services and pipelines to be consumed at web-scale
- Daily Grind: Interface with data scientists, project managers, and the engineering team to achieve sprint goals on the product roadmap, and ensure healthy models, endpoints, CI/CD,
- Career Progression: Senior ML Engineer, ML Architect
YOU CAN EXPECT TO
- Work in a product-development team capable of independently authoring software products.
- Guide junior programmers, set up the architecture, and follow modular development approaches.
- Design and develop code which is well documented.
- Optimize of the application for maximum speed and scalability
- Adhere to the best Information security and Devops practices.
- Research and develop new approaches to problems.
- Design and implement schemas and databases with respect to the AI application
- Cross-pollinated with other teams.
HARD AND SOFT SKILLS
Must Have
- Problem-solving abilities
- Extremely strong programming background – data structures and algorithm
- Advanced Machine Learning: TensorFlow, Keras
- Python, spaCy, NLTK, Word2Vec, Graph databases, Knowledge-graph, BERT (derived models), Hyperparameter tuning
- Experience with OOPs and design patterns
- Exposure to RDBMS/NoSQL
- Test Driven Development Methodology
Good to Have
- Working in cloud-native environments (preferably Azure)
- Microservices
- Enterprise Design Patterns
- Microservices Architecture
- Distributed Systems
As a Data Warehouse Engineer in our team, you should have a proven ability to deliver high-quality work on time and with minimal supervision.
Develops or modifies procedures to solve complex database design problems, including performance, scalability, security and integration issues for various clients (on-site and off-site).
Design, develop, test, and support the data warehouse solution.
Adapt best practices and industry standards, ensuring top quality deliverable''s and playing an integral role in cross-functional system integration.
Design and implement formal data warehouse testing strategies and plans including unit testing, functional testing, integration testing, performance testing, and validation testing.
Evaluate all existing hardware's and software's according to required standards and ability to configure the hardware clusters as per the scale of data.
Data integration using enterprise development tool-sets (e.g. ETL, MDM, Quality, CDC, Data Masking, Quality).
Maintain and develop all logical and physical data models for enterprise data warehouse (EDW).
Contributes to the long-term vision of the enterprise data warehouse (EDW) by delivering Agile solutions.
Interact with end users/clients and translate business language into technical requirements.
Acts independently to expose and resolve problems.
Participate in data warehouse health monitoring and performance optimizations as well as quality documentation.
Job Requirements :
2+ years experience working in software development & data warehouse development for enterprise analytics.
2+ years of working with Python with major experience in Red-shift as a must and exposure to other warehousing tools.
Deep expertise in data warehousing, dimensional modeling and the ability to bring best practices with regard to data management, ETL, API integrations, and data governance.
Experience working with data retrieval and manipulation tools for various data sources like Relational (MySQL, PostgreSQL, Oracle), Cloud-based storage.
Experience with analytic and reporting tools (Tableau, Power BI, SSRS, SSAS). Experience in AWS cloud stack (S3, Glue, Red-shift, Lake Formation).
Experience in various DevOps practices helping the client to deploy and scale the systems as per requirement.
Strong verbal and written communication skills with other developers and business clients.
Knowledge of Logistics and/or Transportation Domain is a plus.
Ability to handle/ingest very huge data sets (both real-time data and batched data) in an efficient manner.