Data Engineer
- High Skilled and proficient on Azure Data Engineering Tech stacks (ADF, Databricks) - Should be well experienced in design and development of Big data integration platform (Kafka, Hadoop). - Highly skilled and experienced in building medium to complex data integration pipelines for Data at Rest and streaming data using Spark. - Strong knowledge in R/Python. - Advanced proficiency in solution design and implementation through Azure Data Lake, SQL and NoSQL Databases. - Strong in Data Warehousing concepts - Expertise in SQL, SQL tuning, Data Management (Data Security), schema design, Python and ETL processes - Highly Motivated, Self-Starter and quick learner - Must have Good knowledge on Data modelling and understating of Data analytics - Exposure to Statistical procedures, Experiments and Machine Learning techniques is an added advantage. - Experience in leading small team of 6/7 Data Engineers. - Excellent written and verbal communication skills
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Position: . Data Engineer
Location: Hyderabad, Telangana, India
Job Type: Permanent (full-time)
Company Description:
We are a Seattle based product engineering, software development and technology services firm with offices in the U.S., Canada, Bulgaria, and India (Manjeera Trinity Corporate, JNTU-Hitech City Road, beside LULU Mall, Hyderabad) . Wallero is a Microsoft Gold partner company. Please find detailed overview About Wallero: https://wallero.com/aboutus/ and Wallero Culture: https://wallero.com/careers/
Job Description:
- Tech stack: Python, Pyspark, Databricks.
- Excellent in the Supply Chain domain.
- Technical expert in the field with the ability to think out of the box.
- Excellent communicator.
- Work autonomously with minimal instructions from JNJ involvement.
- Should be able to guide the team on the best practices (reusable, modularized coding, design patterns, and so on).
If you believe you have the skills and experience necessary for this role and are excited about contributing to our team, we would love to hear from you.
Thank you,
Manu Nakka
Lead Technical Recruiter
Lightning Job By Cutshort ⚡
As part of this feature, you can expect status updates about your application and replies within 72 hours (once the screening questions are answered)
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
Airflow developer:
Exp: 5 to 10yrs & Relevant exp must be above 4 Years.
Work location: Hyderabad (Hybrid Model)
Job description:
· Experience in working on Airflow.
· Experience in SQL, Python, and Object-oriented programming.
· Experience in the data warehouse, database concepts, and ETL tools (Informatica, DataStage, Pentaho, etc.).
· Azure experience and exposure to Kubernetes.
· Experience in Azure data factory, Azure Databricks, and Snowflake.
Required Skills: Azure Databricks/Data Factory, Kubernetes/Dockers, DAG Development, Hands-on Python coding.
- Mandatory - Hands on experience in Python and PySpark.
- Build pySpark applications using Spark Dataframes in Python using Jupyter notebook and PyCharm(IDE).
- Worked on optimizing spark jobs that processes huge volumes of data.
- Hands on experience in version control tools like Git.
- Worked on Amazon’s Analytics services like Amazon EMR, Lambda function etc
- Worked on Amazon’s Compute services like Amazon Lambda, Amazon EC2 and Amazon’s Storage service like S3 and few other services like SNS.
- Experience/knowledge of bash/shell scripting will be a plus.
- Experience in working with fixed width, delimited , multi record file formats etc.
- Hands on experience in tools like Jenkins to build, test and deploy the applications
- Awareness of Devops concepts and be able to work in an automated release pipeline environment.
- Excellent debugging skills.
Job Title: Data Engineer
Job Summary: As a Data Engineer, you will be responsible for designing, building, and maintaining the infrastructure and tools necessary for data collection, storage, processing, and analysis. You will work closely with data scientists and analysts to ensure that data is available, accessible, and in a format that can be easily consumed for business insights.
Responsibilities:
- Design, build, and maintain data pipelines to collect, store, and process data from various sources.
- Create and manage data warehousing and data lake solutions.
- Develop and maintain data processing and data integration tools.
- Collaborate with data scientists and analysts to design and implement data models and algorithms for data analysis.
- Optimize and scale existing data infrastructure to ensure it meets the needs of the business.
- Ensure data quality and integrity across all data sources.
- Develop and implement best practices for data governance, security, and privacy.
- Monitor data pipeline performance / Errors and troubleshoot issues as needed.
- Stay up-to-date with emerging data technologies and best practices.
Requirements:
Bachelor's degree in Computer Science, Information Systems, or a related field.
Experience with ETL tools like Matillion,SSIS,Informatica
Experience with SQL and relational databases such as SQL server, MySQL, PostgreSQL, or Oracle.
Experience in writing complex SQL queries
Strong programming skills in languages such as Python, Java, or Scala.
Experience with data modeling, data warehousing, and data integration.
Strong problem-solving skills and ability to work independently.
Excellent communication and collaboration skills.
Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
Familiarity with data warehouse/Data lake technologies like Snowflake or Databricks
Familiarity with cloud computing platforms such as AWS, Azure, or GCP.
Familiarity with Reporting tools
Teamwork/ growth contribution
- Helping the team in taking the Interviews and identifying right candidates
- Adhering to timelines
- Intime status communication and upfront communication of any risks
- Tech, train, share knowledge with peers.
- Good Communication skills
- Proven abilities to take initiative and be innovative
- Analytical mind with a problem-solving aptitude
Good to have :
Master's degree in Computer Science, Information Systems, or a related field.
Experience with NoSQL databases such as MongoDB or Cassandra.
Familiarity with data visualization and business intelligence tools such as Tableau or Power BI.
Knowledge of machine learning and statistical modeling techniques.
If you are passionate about data and want to work with a dynamic team of data scientists and analysts, we encourage you to apply for this position.
Skill- Spark and Scala along with Azure
Location - Pan India
Looking for someone Bigdata along with Azure
Key Responsibilities : ( Data Developer Python, Spark)
Exp : 2 to 9 Yrs
Development of data platforms, integration frameworks, processes, and code.
Develop and deliver APIs in Python or Scala for Business Intelligence applications build using a range of web languages
Develop comprehensive automated tests for features via end-to-end integration tests, performance tests, acceptance tests and unit tests.
Elaborate stories in a collaborative agile environment (SCRUM or Kanban)
Familiarity with cloud platforms like GCP, AWS or Azure.
Experience with large data volumes.
Familiarity with writing rest-based services.
Experience with distributed processing and systems
Experience with Hadoop / Spark toolsets
Experience with relational database management systems (RDBMS)
Experience with Data Flow development
Knowledge of Agile and associated development techniques including:
n
- Key Responsibilities : Use cases to support use case analysis E2E, define capabilities, understand the data and model Machine Learning Operations MLOps Azure Machine Learning, Azure Cognitive Services, Azure DevOps, Overall Azure Cloud Experience, Powershell, DSVM, AML Compute / Training Clusters Azure Infrastructure Experience, Python, Big Data Python Scripting 8 Automate ML models deployments, Manage, monitor, troubleshoot machine learning infrastructure and Setup ML Pipe lines
- Technical Experience : Proven skills experience in Azure AI ML solution design and architecture based solution using Azure Cloud capabilities AML / AKS Proven record of embedding advanced analytical models into business processes Collaborate in multi-functional teams to evaluate business activities, and then develop innovative and effective approaches to tackle teams analytics problems and communicate results bitbucket, Nodejs, PowerBI SQL, Python
- Experience in setting up MLOps framework for AI ML team
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.