11+ ER/Studio Jobs in India

Desired Competencies:

Ø  Expertise in Azure Data Factory V2

Ø  Expertise in other Azure components like Data lake Store, SQL Database, Databricks

Ø  Must have working knowledge of spark programming

Ø  Good exposure to Data Projects dealing with Data Design and Source to Target documentation including defining transformation rules

Ø  Strong knowledge of CICD Process

Ø  Experience in building power BI reports

Ø  Understanding of different components like Pipelines, activities, datasets & linked services

Ø  Exposure to dynamic configuration of pipelines using data sets and linked Services

Ø  Experience in designing, developing and deploying pipelines to higher environments

Ø  Good knowledge on File formats for flexible usage, File location Objects (SFTP, FTP, local, HDFS, ADLS, BLOB, Amazon S3 etc.)

Ø  Strong knowledge in SQL queries

Ø  Must have worked in full life-cycle development from functional design to deployment

Ø  Should have working knowledge of GIT, SVN

Ø  Good experience in establishing connection with heterogeneous sources like Hadoop, Hive, Amazon, Azure, Salesforce, SAP, HANA, API’s, various Databases etc.

Ø  Should have working knowledge of different resources available in Azure like Storage Account, Synapse, Azure SQL Server, Azure Data Bricks, Azure Purview

Ø  Any experience related to metadata management, data modelling, and related tools (Erwin or ER Studio or others) would be preferred

Preferred Qualifications:

Ø  Bachelor's degree in Computer Science or Technology

Ø  Proven success in contributing to a team-oriented environment

Ø  Proven ability to work creatively and analytically in a problem-solving environment

Ø  Excellent communication (written and oral) and interpersonal skills

Qualifications

BE/BTECH

KEY RESPONSIBILITIES :

Location – Bangalore

Responsibilities include: 

• Convert the machine learning models into application program interfaces (APIs) so that other applications can use it
• Build AI models from scratch and help the different components of the organization (such as product managers and stakeholders) understand what results they gain from the model
• Build data ingestion and data transformation infrastructure
• Automate infrastructure that the data science team uses
• Perform statistical analysis and tune the results so that the organization can make better-informed decisions
• Set up and manage AI development and product infrastructure
• Be a good team player, as coordinating with others is a must

Job Description

Mandatory Requirements 

• Experience in AWS Glue

• Experience in Apache Parquet 

• Proficient in AWS S3 and data lake 

• Knowledge of Snowflake

• Understanding of file-based ingestion best practices.

• Scripting language - Python & pyspark

CORE RESPONSIBILITIES

• Create and manage cloud resources in AWS 

• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 

• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 

• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 

• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.

• Define process improvement opportunities to optimize data collection, insights and displays.

• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 

• Identify and interpret trends and patterns from complex data sets 

• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 

• Key participant in regular Scrum ceremonies with the agile teams  

• Proficient at developing queries, writing reports and presenting findings 

• Mentor junior members and bring best industry practices.

QUALIFICATIONS

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 

• Strong background in math, statistics, computer science, data science or related discipline

• Advanced knowledge one of language: Java, Scala, Python, C# 

• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  

• Proficient with

• Data mining/programming tools (e.g. SAS, SQL, R, Python)

• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)

• Data visualization (e.g. Tableau, Looker, MicroStrategy)

• Comfortable learning about and deploying new technologies and tools. 

• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 

• Good written and oral communication skills and ability to present results to non-technical audiences 

• Knowledge of business intelligence and analytical tools, technologies and techniques.

Familiarity and experience in the following is a plus: 

• AWS certification

• Spark Streaming 

• Kafka Streaming / Kafka Connect 

• ELK Stack 

• Cassandra / MongoDB 

• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

JD Code: SHI-LDE-01 

Version#: 1.0 

Date of JD Creation: 27-March-2023 

Position Title: Lead Data Engineer 

Reporting to: Technical Director 

Location: Bangalore Urban, India (on-site) 

SmartHub.ai (www.smarthub.ai) is a fast-growing Startup headquartered in Palo Alto, CA, and with offices in Seattle and Bangalore. We operate at the intersection of AI, IoT & Edge Computing. With strategic investments from leaders in infrastructure & data management, SmartHub.ai is redefining the Edge IoT space. Our “Software Defined Edge” products help enterprises rapidly accelerate their Edge Infrastructure Management & Intelligence. We empower enterprises to leverage their Edge environment to increase revenue, efficiency of operations, manage safety and digital risks by using Edge and AI technologies. 

SmartHub is an equal opportunity employer and will always be committed to nurture a workplace culture that supports, inspires and respects all individuals, encourages employees to bring their best selves to work, laugh and share. We seek builders who hail from a variety of backgrounds, perspectives and skills to join our team.  

Summary 

This role requires the candidate to translate business and product requirements to build, maintain, optimize data systems which can be relational or non-relational in nature. The candidate is expected to tune and analyse the data including from a short and long-term trend analysis and reporting, AI/ML uses cases. 

We are looking for a talented technical professional with at least 8 years of proven experience in owning, architecting, designing, operating and optimising databases that are used for large scale analytics and reports. 

Responsibilities 

• Provide technical & architectural leadership for the next generation of product development. 
• Innovate, Research & Evaluate new technologies and tools for a quality output. 
• Architect, Design and Implement ensuring scalability, performance and security. 
• Code and implement new algorithms to solve complex problems. 
• Analyze complex data, develop, optimize and transform large data sets both structured and unstructured. 
• Ability to deploy and administrator the database and continuously tuning for performance especially container orchestration stacks such as Kubernetes  
• Develop analytical models and solutions Mentor Junior members technically in Architecture, Designing and robust Coding. 
• Work in an Agile development environment while continuously evaluating and improvising engineering processes 

Required 

• At least 8 years of experience with significant depth in designing and building scalable distributed database systems for enterprise class products, experience of working in product development companies. 
• Should have been feature/component lead for several complex features involving large datasets. 
• Strong background in relational and non-relational database like Postgres, MongoDB, Hadoop etl. 
• Deep exp database optimization, tuning ertise in SQL, Time Series Databases, Apache Drill, HDFS, Spark are good to have 
• Excellent analytical and problem-solving skill sets. 
• Experience in  for high throughput is highly desirable 
• Exposure to database provisioning in Kubernetes/non-Kubernetes environments, configuration and tuning in a highly available mode. 
• Demonstrated ability to provide technical leadership and mentoring to the team 

Title: Data Engineer (Azure) (Location: Gurgaon/Hyderabad)

Salary: Competitive as per Industry Standard

We are expanding our Data Engineering Team and hiring passionate professionals with extensive

knowledge and experience in building and managing large enterprise data and analytics platforms. We

are looking for creative individuals with strong programming skills, who can understand complex

business and architectural problems and develop solutions. The individual will work closely with the rest

of our data engineering and data science team in implementing and managing Scalable Smart Data

Lakes, Data Ingestion Platforms, Machine Learning and NLP based Analytics Platforms, Hyper-Scale

Processing Clusters, Data Mining and Search Engines.

What You’ll Need:

• 3+ years of industry experience in creating and managing end-to-end Data Solutions, Optimal

Data Processing Pipelines and Architecture dealing with large volume, big data sets of varied

data types.

• Proficiency in Python, Linux and shell scripting.
• Strong knowledge of working with PySpark dataframes, Pandas dataframes for writing efficient pre-processing and other data manipulation tasks.
  ● Strong experience in developing the infrastructure required for data ingestion, optimal

extraction, transformation, and loading of data from a wide variety of data sources using tools like Azure Data Factory,  Azure Databricks (or Jupyter notebooks/ Google Colab) (or other similiar tools).

• Working knowledge of github or other version control tools.
• Experience with creating Restful web services and API platforms.
• Work with data science and infrastructure team members to implement practical machine

learning solutions and pipelines in production.

• Experience with cloud providers like Azure/AWS/GCP.
• Experience with SQL and NoSQL databases. MySQL/ Azure Cosmosdb / Hbase/MongoDB/ Elasticsearch etc.
• Experience with stream-processing systems: Spark-Streaming, Kafka etc and working experience with event driven architectures.
• Strong analytic skills related to working with unstructured datasets.

Good to have (to filter or prioritize candidates)

• Experience with testing libraries such as pytest for writing unit-tests for the developed code.
• Knowledge of Machine Learning algorithms and libraries would be good to have,

implementation experience would be an added advantage.

• Knowledge and experience of Datalake, Dockers and Kubernetes would be good to have.
• Knowledge of Azure functions , Elastic search etc will be good to have.

• Having experience with model versioning (mlflow) and data versioning will be beneficial
• Having experience with microservices libraries or with python libraries such as flask for hosting ml services and models would be great.

JD for IOT DE:

The role requires experience in Azure core technologies – IoT Hub/ Event Hub, Stream Analytics, IoT Central, Azure Data Lake Storage, Azure Cosmos, Azure Data Factory, Azure SQL Database, Azure HDInsight / Databricks, SQL data warehouse.

You Have:

• Minimum 2 years of software development experience
• Minimum 2 years of experience in IoT/streaming data pipelines solution development
• Bachelor's and/or Master’s degree in computer science
• Strong Consulting skills in data management including data governance, data quality, security, data integration, processing, and provisioning
• Delivered data management projects with real-time/near real-time data insights delivery on Azure Cloud
• Translated complex analytical requirements into the technical design including data models, ETLs, and Dashboards / Reports
• Experience deploying dashboards and self-service analytics solutions on both relational and non-relational databases
• Experience with different computing paradigms in databases such as In-Memory, Distributed, Massively Parallel Processing
• Successfully delivered large scale IOT data management initiatives covering Plan, Design, Build and Deploy phases leveraging different delivery methodologies including Agile
• Experience in handling telemetry data with Spark Streaming, Kafka, Flink, Scala, Pyspark, Spark SQL.
• Hands-on experience on containers and Dockers
• Exposure to streaming protocols like MQTT and AMQP
• Knowledge of OT network protocols like OPC UA, CAN Bus, and similar protocols
• Strong knowledge of continuous integration, static code analysis, and test-driven development
• Experience in delivering projects in a highly collaborative delivery model with teams at onsite and offshore
• Must have excellent analytical and problem-solving skills
• Delivered change management initiatives focused on driving data platforms adoption across the enterprise
• Strong verbal and written communications skills are a must, as well as the ability to work effectively across internal and external organizations
   

Roles & Responsibilities
 

You Will:

• Translate functional requirements into technical design
• Interact with clients and internal stakeholders to understand the data and platform requirements in detail and determine core Azure services needed to fulfill the technical design
• Design, Develop and Deliver data integration interfaces in ADF and Azure Databricks
• Design, Develop and Deliver data provisioning interfaces to fulfill consumption needs
• Deliver data models on Azure platform, it could be on Azure Cosmos, SQL DW / Synapse, or SQL
• Advise clients on ML Engineering and deploying ML Ops at Scale on AKS
• Automate core activities to minimize the delivery lead times and improve the overall quality
• Optimize platform cost by selecting the right platform services and architecting the solution in a cost-effective manner
• Deploy Azure DevOps and CI CD processes
• Deploy logging and monitoring across the different integration points for critical alerts

REQUIREMENT:

•  Previous experience of working in large scale data engineering
•  4+ years of experience working in data engineering and/or backend technologies with cloud experience (any) is mandatory.
•  Previous experience of architecting and designing backend for large scale data processing.
•  Familiarity and experience of working in different technologies related to data engineering – different database technologies, Hadoop, spark, storm, hive etc.
•  Hands-on and have the ability to contribute a key portion of data engineering backend.
•  Self-inspired and motivated to drive for exceptional results.
•  Familiarity and experience working with different stages of data engineering – data acquisition, data refining, large scale data processing, efficient data storage for business analysis.
•  Familiarity and experience working with different DB technologies and how to scale them.

RESPONSIBILITY:

•  End to end responsibility to come up with data engineering architecture, design, development and then implementation of it.
•  Build data engineering workflow for large scale data processing.
•  Discover opportunities in data acquisition.
•  Bring industry best practices for data engineering workflow.
•  Develop data set processes for data modelling, mining and production.
•  Take additional tech responsibilities for driving an initiative to completion
•  Recommend ways to improve data reliability, efficiency and quality
•  Goes out of their way to reduce complexity.
•  Humble and outgoing - engineering cheerleaders.