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Blenheim Chalcot IT Services India Pvt Ltd
Data Warehouse and Analytics solutions that aggregate data across diverse sources and data types
including text, video and audio through to live stream and IoT in an agile project delivery
environment with a focus on DataOps and Data Observability. You will work with Azure SQL
Databases, Synapse Analytics, Azure Data Factory, Azure Datalake Gen2, Azure Databricks, Azure
Machine Learning, Azure Service Bus, Azure Serverless (LogicApps, FunctionApps), Azure Data
Catalogue and Purview among other tools, gaining opportunities to learn some of the most
advanced and innovative techniques in the cloud data space.
You will be building Power BI based analytics solutions to provide actionable insights into customer
data, and to measure operational efficiencies and other key business performance metrics.
You will be involved in the development, build, deployment, and testing of customer solutions, with
responsibility for the design, implementation and documentation of the technical aspects, including
integration to ensure the solution meets customer requirements. You will be working closely with
fellow architects, engineers, analysts, and team leads and project managers to plan, build and roll
out data driven solutions
Expertise:
Proven expertise in developing data solutions with Azure SQL Server and Azure SQL Data Warehouse (now
Synapse Analytics)
Demonstrated expertise of data modelling and data warehouse methodologies and best practices.
Ability to write efficient data pipelines for ETL using Azure Data Factory or equivalent tools.
Integration of data feeds utilising both structured (ex XML/JSON) and flat schemas (ex CSV,TXT,XLSX)
across a wide range of electronic delivery mechanisms (API/SFTP/etc )
Azure DevOps knowledge essential for CI/CD of data ingestion pipelines and integrations.
Experience with object-oriented/object function scripting languages such as Python, Java, JavaScript, C#,
Scala, etc is required.
Expertise in creating technical and Architecture documentation (ex: HLD/LLD) is a must.
Proven ability to rapidly analyse and design solution architecture in client proposals is an added advantage.
Expertise with big data tools: Hadoop, Spark, Kafka, NoSQL databases, stream-processing systems is a plus.
Essential Experience:
5 or more years of hands-on experience in a data architect role with the development of ingestion,
integration, data auditing, reporting, and testing with Azure SQL tech stack.
full data and analytics project lifecycle experience (including costing and cost management of data
solutions) in Azure PaaS environment is essential.
Microsoft Azure and Data Certifications, at least fundamentals, are a must.
Experience using agile development methodologies, version control systems and repositories is a must.
A good, applied understanding of the end-to-end data process development life cycle.
A good working knowledge of data warehouse methodology using Azure SQL.
A good working knowledge of the Azure platform, it’s components, and the ability to leverage it’s
resources to implement solutions is a must.
Experience working in the Public sector or in an organisation servicing Public sector is a must,
Ability to work to demanding deadlines, keep momentum and deal with conflicting priorities in an
environment undergoing a programme of transformational change.
The ability to contribute and adhere to standards, have excellent attention to detail and be strongly driven
by quality.
Desirables:
Experience with AWS or google cloud platforms will be an added advantage.
Experience with Azure ML services will be an added advantage Personal Attributes
Articulated and clear in communications to mixed audiences- in writing, through presentations and one-toone.
Ability to present highly technical concepts and ideas in a business-friendly language.
Ability to effectively prioritise and execute tasks in a high-pressure environment.
Calm and adaptable in the face of ambiguity and in a fast-paced, quick-changing environment
Extensive experience working in a team-oriented, collaborative environment as well as working
independently.
Comfortable with multi project multi-tasking consulting Data Architect lifestyle
Excellent interpersonal skills with teams and building trust with clients
Ability to support and work with cross-functional teams in a dynamic environment.
A passion for achieving business transformation; the ability to energise and excite those you work with
Initiative; the ability to work flexibly in a team, working comfortably without direct supervision.
Responsibilities
- Work on execution and scheduling of all tasks related to assigned projects' deliverable dates
- Optimize and debug existing codes to make them scalable and improve performance
- Design, development, and delivery of tested code and machine learning models into production environments
- Work effectively in teams, managing and leading teams
- Provide effective, constructive feedback to the delivery leader
- Manage client expectations and work with an agile mindset with machine learning and AI technology
- Design and prototype data-driven solutions
Eligibility
- Highly experienced in designing, building, and shipping scalable and production-quality machine learning algorithms in the field of Python applications
- Working knowledge and experience in NLP core components (NER, Entity Disambiguation, etc.)
- In-depth expertise in Data Munging and Storage (Experienced in SQL, NoSQL, MongoDB, Graph Databases)
- Expertise in writing scalable APIs for machine learning models
- Experience with maintaining code logs, task schedulers, and security
- Working knowledge of machine learning techniques, feed-forward, recurrent and convolutional neural networks, entropy models, supervised and unsupervised learning
- Experience with at least one of the following: Keras, Tensorflow, Caffe, or PyTorch
Job Title: Data Analyst with Python
Experience: 4+ years
Location: Mumbai
Working Mode: Onsite
Primary Skills: Python, Data Analysis of RDs, FDs, Saving Accounts, Banking domain, Risk Consultant, Car Loan Model, Cross-sell model
Qualification: Any graduation
Job Description
1. With 4 to 5 years of banking analytics experience
2. Data Analyst profile with good domain understanding
3. Good with Python and worked on Liabilities (Mandatory)
4. For Liabilities Should have worked on (Saving A/c, FD,RD) (Mandatory)
5. Good with stakeholder management and requirement gathering
6. Only from banking industry
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.
We are looking out for a Snowflake developer for one of our premium clients for their PAN India loaction
Responsibilities :
- Involve in planning, design, development and maintenance of large-scale data repositories, pipelines, analytical solutions and knowledge management strategy
- Build and maintain optimal data pipeline architecture to ensure scalability, connect operational systems data for analytics and business intelligence (BI) systems
- Build data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
- Reporting and obtaining insights from large data chunks on import/export and communicating relevant pointers for helping in decision-making
- Preparation, analysis, and presentation of reports to the management for further developmental activities
- Anticipate, identify and solve issues concerning data management to improve data quality
Requirements :
- Ability to build and maintain ETL pipelines
- Technical Business Analysis experience and hands-on experience developing functional spec
- Good understanding of Data Engineering principles including data modeling methodologies
- Sound understanding of PostgreSQL
- Strong analytical and interpersonal skills as well as reporting capabilities
Understand various raw data input formats, build consumers on Kafka/ksqldb for them and ingest large amounts of raw data into Flink and Spark.
Conduct complex data analysis and report on results.
Build various aggregation streams for data and convert raw data into various logical processing streams.
Build algorithms to integrate multiple sources of data and create a unified data model from all the sources.
Build a unified data model on both SQL and NO-SQL databases to act as data sink.
Communicate the designs effectively with the fullstack engineering team for development.
Explore machine learning models that can be fitted on top of the data pipelines.
Mandatory Qualifications Skills:
Deep knowledge of Scala and Java programming languages is mandatory
Strong background in streaming data frameworks (Apache Flink, Apache Spark) is mandatory
Good understanding and hands on skills on streaming messaging platforms such as Kafka
Familiarity with R, C and Python is an asset
Analytical mind and business acumen with strong math skills (e.g. statistics, algebra)
Problem-solving aptitude
Excellent communication and presentation skills