Technical Architect

Lightning Job By Cutshort ⚡

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About Databook:-

- Great salespeople let their customers’ strategies do the talking.

Databook’s award-winning Strategic Relationship Management (SRM) platform uses advanced AI and NLP to empower the world’s largest B2B sales teams to create, manage, and maintain strategic relationships at scale. The platform ingests and interprets billions of financial and market data signals to generate actionable sales strategies that connect the seller’s solutions to a buyer’s financial pain and urgency.

The Opportunity

We're seeking Junior Engineers to support and develop Databook’s capabilities. Working closely with our seasoned engineers, you'll contribute to crafting new features and ensuring our platform's reliability. If you're eager about playing a part in building the future of customer intelligence, with a keen eye towards quality, we'd love to meet you!

Specifically, you'll

- Participate in various stages of the engineering lifecycle alongside our experienced engineers.

- Assist in maintaining and enhancing features of the Databook platform.

- Collaborate with various teams to comprehend requirements and aid in implementing technology solutions.

Please note: As you progress and grow with us, you might be introduced to on-call rotations to handle any platform challenges.

Working Arrangements:

- This position offers a hybrid work mode, allowing employees to work both remotely and in-office as mutually agreed upon.

What we're looking for

- 1-2+ years experience as a Data Engineer

- Bachelor's degree in Engineering

- Willingness to work across different time zones

- Ability to work independently

- Knowledge of cloud (AWS or Azure)

- Exposure to distributed systems such as Spark, Flink or Kafka

- Fundamental knowledge of data modeling and optimizations

- Minimum of one year of experience using Python working as a Software Engineer

- Knowledge of SQL (Postgres) databases would be beneficial

- Experience with building analytics dashboard

- Familiarity with RESTful APIs and/or GraphQL is welcomed

- Hand-on experience with Numpy, Pandas, SpaCY would be a plus

- Exposure or working experience on GenAI (LLMs in general), LLMOps would be a plus

- Highly fluent in both spoken and written English language

Ideal candidates will also have:

- Self-motivated with great organizational skills.

- Ability to focus on small and subtle details.

- Are willing to learn and adapt in a rapidly changing environment.

- Excellent written and oral communication skills.

Join us and enjoy these perks!

- Competitive salary with bonus

- Medical insurance coverage

- 5 weeks leave plus public holidays

- Employee referral bonus program

- Annual learning stipend to spend on books, courses or other training materials that help you develop skills relevant to your role or professional development

- Complimentary subscription to Masterclass

Roles and Responsibilities:

• Design, develop, and maintain the end-to-end MLOps infrastructure from the ground up, leveraging open-source systems across the entire MLOps landscape.
• Creating pipelines for data ingestion, data transformation, building, testing, and deploying machine learning models, as well as monitoring and maintaining the performance of these models in production.
• Managing the MLOps stack, including version control systems, continuous integration and deployment tools, containerization, orchestration, and monitoring systems.
• Ensure that the MLOps stack is scalable, reliable, and secure.

Skills Required:

• 3-6 years of MLOps experience
• Preferably worked in the startup ecosystem

Primary Skills:

• Experience with E2E MLOps systems like ClearML, Kubeflow, MLFlow etc.
• Technical expertise in MLOps: Should have a deep understanding of the MLOps landscape and be able to leverage open-source systems to build scalable, reliable, and secure MLOps infrastructure.
• Programming skills: Proficient in at least one programming language, such as Python, and have experience with data science libraries, such as TensorFlow, PyTorch, or Scikit-learn.
• DevOps experience: Should have experience with DevOps tools and practices, such as Git, Docker, Kubernetes, and Jenkins.

Secondary Skills:

• Version Control Systems (VCS) tools like Git and Subversion
• Containerization technologies like Docker and Kubernetes
• Cloud Platforms like AWS, Azure, and Google Cloud Platform
• Data Preparation and Management tools like Apache Spark, Apache Hadoop, and SQL databases like PostgreSQL and MySQL
• Machine Learning Frameworks like TensorFlow, PyTorch, and Scikit-learn
• Monitoring and Logging tools like Prometheus, Grafana, and Elasticsearch
• Continuous Integration and Continuous Deployment (CI/CD) tools like Jenkins, GitLab CI, and CircleCI
• Explain ability and Interpretability tools like LIME and SHAP

Job Overview

We are looking for a Data Engineer to join our data team to solve data-driven critical

business problems. The hire will be responsible for expanding and optimizing the existing

end-to-end architecture including the data pipeline architecture. The Data Engineer will

collaborate with software developers, database architects, data analysts, data scientists and platform team on data initiatives and will ensure optimal data delivery architecture is

consistent throughout ongoing projects. The right candidate should have hands on in

developing a hybrid set of data-pipelines depending on the business requirements.

Responsibilities

• Develop, construct, test and maintain existing and new data-driven architectures.
• Align architecture with business requirements and provide solutions which fits best
• to solve the business problems.
• Build the infrastructure required for optimal extraction, transformation, and loading
• of data from a wide variety of data sources using SQL and Azure ‘big data’
• technologies.
• Data acquisition from multiple sources across the organization.
• Use programming language and tools efficiently to collate the data.
• Identify ways to improve data reliability, efficiency and quality
• Use data to discover tasks that can be automated.
• Deliver updates to stakeholders based on analytics.
• Set up practices on data reporting and continuous monitoring
  
  

Required Technical Skills

• Graduate in Computer Science or in similar quantitative area
• 1+ years of relevant work experience as a Data Engineer or in a similar role.
• Advanced SQL knowledge, Data-Modelling and experience working with relational
• databases, query authoring (SQL) as well as working familiarity with a variety of
• databases.
• Experience in developing and optimizing ETL pipelines, big data pipelines, and datadriven
• architectures.
• Must have strong big-data core knowledge & experience in programming using Spark - Python/Scala
• Experience with orchestrating tool like Airflow or similar
• Experience with Azure Data Factory is good to have
• Build processes supporting data transformation, data structures, metadata,
• dependency and workload management.
• Experience supporting and working with cross-functional teams in a dynamic
• environment.
• Good understanding of Git workflow, Test-case driven development and using CICD
• is good to have
• Good to have some understanding of Delta tables It would be advantage if the candidate also have below mentioned experience using
• the following software/tools:
• Experience with big data tools: Hadoop, Spark, Hive, etc.
• Experience with relational SQL and NoSQL databases
• Experience with cloud data services
• Experience with object-oriented/object function scripting languages: Python, Scala, etc.

Role Description:

• You will be part of the data delivery team and will have the opportunity to develop a deep understanding of the domain/function.
• You will design and drive the work plan for the optimization/automation and standardization of the processes incorporating best practices to achieve efficiency gains.
• You will run data engineering pipelines, link raw client data with data model, conduct data assessment, perform data quality checks, and transform data using ETL tools.
• You will perform data transformations, modeling, and validation activities, as well as configure applications to the client context. You will also develop scripts to validate, transform, and load raw data using programming languages such as Python and / or PySpark.
• In this role, you will determine database structural requirements by analyzing client operations, applications, and programming.
• You will develop cross-site relationships to enhance idea generation, and manage stakeholders.
• Lastly, you will collaborate with the team to support ongoing business processes by delivering high-quality end products on-time and perform quality checks wherever required.

We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Roles and Responsibilities:

• Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
• Develop programs in Scala and Python as part of data cleaning and processing.
• Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.  
• Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
• Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Provide high operational excellence guaranteeing high availability and platform stability.
• Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Skills:

• Experience with Big Data pipeline, Big Data analytics, Data warehousing.
• Experience with SQL/No-SQL, schema design and dimensional data modeling.
• Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
• Experience in designing systems that process structured as well as unstructured data at large scale.
• Experience in AWS/Spark/Java/Scala/Python development.
• Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
• Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
• Prior exposure to streaming data sources such as Kafka.
• Should have knowledge on Shell Scripting and Python scripting.
• High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
• Experience with NoSQL databases such as Cassandra / MongoDB.
• Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
• Experience building and deploying applications on on-premise and cloud-based infrastructure.
• Having a good understanding of machine learning landscape and concepts. 

Qualifications and Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.

Certifications:

Good to have at least one of the Certifications listed here:

    AZ 900 - Azure Fundamentals

    DP 200, DP 201, DP 203, AZ 204 - Data Engineering

    AZ 400 - Devops Certification

Qentelli is seeking a Solution Architect to untangle and redesign a huge granny old monolithic legacy system. Interesting part is that the new system should be commissioned module by module and legacy system should phase off accordingly. So your design will have a cutting edge future state and a transition state to get there. Implementation now is all Microsoft tech stack and will continue to be on newer Microsoft tech stack. Also there is a critical component of API management to be introduced into the solution. Performance and scalability will be at the center of your solution architecture. Data modelling is one thing that is of super high importance to know.

You’ll have a distributed team with onshore in the US and offshore in India. As a Solution Architect, you should be able to wear multiple hats of working with client on solutioning and getting it implemented by engineering and infrastructure teams that are both onshore and offshore. Right candidate will be awesome at fleshing out and documenting every finer detail of the solution, elaborate at communicating with your teams, disciplined at getting it implemented and passionate for client success.

TECHNOLOGIES YOU’LL NEED TO KNOW

Greetings from Qentelli Solutions Private Limited!

We are hiring for PostgreSQL Developer

Experience: 4 to 12 years

Job Location: Hyderabad

Job Description:

• Experience in RDBMS (PostgreSQL preferred), Database Backend development, Data Modelling, Performance Tuning, exposure to NoSQL DB, Kubernetes or Cloud (AWS/Azure/GCS)

Skillset for Developer-II:

• Experience on any Big Data Tools (Nifi, Kafka, Spark, sqoop, storm, snowflake), Database Backend development, Python, No SQL DB, API Exposure, cloud or Kubernetes exposure

Skillset for API Developer:

• API Development with extensive knowledge on any RDBMS (preferred PostgreSQL), exposure to cloud or Kubernetes

Required skill

• Around 6- 8.5 years of experience and around 4+ years in AI / Machine learning space
• Extensive experience in designing large scale machine learning solution for the ML use case,  large scale deployments and establishing continues automated improvement / retraining framework.
• Strong experience in Python and Java is required.
• Hands on experience on Scikit-learn, Pandas, NLTK
• Experience in Handling of Timeseries data and associated techniques like Prophet, LSTM
• Experience in Regression, Clustering, classification algorithms
• Extensive experience in buildings traditional Machine Learning SVM, XGBoost, Decision tree and Deep Neural Network models like RNN, Feedforward is required.
• Experience in AutoML like TPOT or other
• Must have strong hands on experience in Deep learning frameworks like Keras, TensorFlow or PyTorch 
• Knowledge of Capsule Network or reinforcement learning, SageMaker is a desirable skill
• Understanding of Financial domain is desirable skill

 Responsibilities 

• Design and implementation of solutions for ML Use cases
• Productionize System and Maintain those
• Lead and implement data acquisition process for ML work
• Learn new methods and model quickly and utilize those in solving use cases

• Research and test novel machine learning approaches for analysing large-scale distributed computing applications.
• Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy,  efficacy, and robustness
• Work closely with other functional teams to integrate implemented systems into the SaaS platform
• Suggest innovative and creative concepts and ideas that would improve the overall platform

‍

The ideal candidate must have the following qualifications:

• 5 + years experience in practical implementation and deployment of large customer-facing ML based systems.
• MS or M Tech (preferred) in applied mathematics/statistics;  CS or Engineering disciplines are acceptable but must have with strong quantitative and applied mathematical skills
• In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python is a must
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

Most importantly, you should be someone who is passionate about building new and innovative products that solve tough real-world problems.

Chennai, India