About Skanda Projects
About Slintel (a 6sense company) :
Slintel, a 6sense company, the leader in capturing technographics-powered buying intent, helps companies uncover the 3% of active buyers in their target market. Slintel evaluates over 100 billion data points and analyzes factors such as buyer journeys, technology adoption patterns, and other digital footprints to deliver market & sales intelligence.
Slintel's customers have access to the buying patterns and contact information of more than 17 million companies and 250 million decision makers across the world.
Slintel is a fast growing B2B SaaS company in the sales and marketing tech space. We are funded by top tier VCs, and going after a billion dollar opportunity. At Slintel, we are building a sales development automation platform that can significantly improve outcomes for sales teams, while reducing the number of hours spent on research and outreach.
We are a big data company and perform deep analysis on technology buying patterns, buyer pain points to understand where buyers are in their journey. Over 100 billion data points are analyzed every week to derive recommendations on where companies should focus their marketing and sales efforts on. Third party intent signals are then clubbed with first party data from CRMs to derive meaningful recommendations on whom to target on any given day.
6sense is headquartered in San Francisco, CA and has 8 office locations across 4 countries.
6sense, an account engagement platform, secured $200 million in a Series E funding round, bringing its total valuation to $5.2 billion 10 months after its $125 million Series D round. The investment was co-led by Blue Owl and MSD Partners, among other new and existing investors.
Linkedin (Slintel) : https://www.linkedin.com/company/slintel/
Industry : Software Development
Company size : 51-200 employees (189 on LinkedIn)
Headquarters : Mountain View, California
Founded : 2016
Specialties : Technographics, lead intelligence, Sales Intelligence, Company Data, and Lead Data.
Website (Slintel) : https://www.slintel.com/slintel
Linkedin (6sense) : https://www.linkedin.com/company/6sense/
Industry : Software Development
Company size : 501-1,000 employees (937 on LinkedIn)
Headquarters : San Francisco, California
Founded : 2013
Specialties : Predictive intelligence, Predictive marketing, B2B marketing, and Predictive sales
Website (6sense) : https://6sense.com/
Acquisition News :
Funding Details & News :
Slintel funding : https://www.crunchbase.com/organization/slintel
6sense funding : https://www.crunchbase.com/organization/6sense
Slintel & 6sense Customers :
About the job
- Work in collaboration with the application team and integration team to design, create, and maintain optimal data pipeline architecture and data structures for Data Lake/Data Warehouse
- Work with stakeholders including the Sales, Product, and Customer Support teams to assist with data-related technical issues and support their data analytics needs
- Assemble large, complex data sets from third-party vendors to meet business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Elastic search, MongoDB, and AWS technology
- Streamline existing and introduce enhanced reporting and analysis solutions that leverage complex data sources derived from multiple internal systems
- 3+ years of experience in a Data Engineer role
- Proficiency in Linux
- Must have SQL knowledge and experience working with relational databases, query authoring (SQL) as well as familiarity with databases including Mysql, Mongo, Cassandra, and Athena
- Must have experience with Python/ Scala
- Must have experience with Big Data technologies like Apache Spark
- Must have experience with Apache Airflow
- Experience with data pipeline and ETL tools like AWS Glue
- Experience working with AWS cloud services: EC2 S3 RDS, Redshift and other Data solutions eg. Databricks, Snowflake
Desired Skills and Experience
Python, SQL, Scala, Spark, ETL
THE ROLE:Sr. Cloud Data Infrastructure Engineer
As a Sr. Cloud Data Infrastructure Engineer with Intuitive, you will be responsible for building or converting legacy data pipelines from legacy environments to modern cloud environments to help the analytics and data science initiatives across our enterprise customers. You will be working closely with SMEs in Data Engineering and Cloud Engineering, to create solutions and extend Intuitive's DataOps Engineering Projects and Initiatives. The Sr. Cloud Data Infrastructure Engineer will be a central critical role for establishing the DataOps/DataX data logistics and management for building data pipelines, enforcing best practices, ownership for building complex and performant Data Lake Environments, work closely with Cloud Infrastructure Architects and DevSecOps automation teams. The Sr. Cloud Data Infrastructure Engineer is the main point of contact for all things related to DataLake formation and data at scale. In this role, we expect our DataOps leaders to be obsessed with data and providing insights to help our end customers.
ROLES & RESPONSIBILITIES:
- Design, develop, implement, and tune large-scale distributed systems and pipelines that process large volume of data; focusing on scalability, low-latency, and fault-tolerance in every system built
- Developing scalable and re-usable frameworks for ingesting large data from multiple sources.
- Modern Data Orchestration engineering - query tuning, performance tuning, troubleshooting, and debugging big data solutions.
- Provides technical leadership, fosters a team environment, and provides mentorship and feedback to technical resources.
- Deep understanding of ETL/ELT design methodologies, patterns, personas, strategy, and tactics for complex data transformations.
- Data processing/transformation using various technologies such as spark and cloud Services.
- Understand current data engineering pipelines using legacy SAS tools and convert to modern pipelines.
Data Infrastructure Engineer Strategy Objectives: End to End Strategy
Define how data is acquired, stored, processed, distributed, and consumed.
Collaboration and Shared responsibility across disciplines as partners in delivery for progressing our maturity model in the End-to-End Data practice.
- Understanding and experience with modern cloud data orchestration and engineering for one or more of the following cloud providers - AWS, Azure, GCP.
- Leading multiple engagements to design and develop data logistic patterns to support data solutions using data modeling techniques (such as file based, normalized or denormalized, star schemas, schema on read, Vault data model, graphs) for mixed workloads, such as OLTP, OLAP, streaming using any formats (structured, semi-structured, unstructured).
- Applying leadership and proven experience with architecting and designing data implementation patterns and engineered solutions using native cloud capabilities that span data ingestion & integration (ingress and egress), data storage (raw & cleansed), data prep & processing, master & reference data management, data virtualization & semantic layer, data consumption & visualization.
- Implementing cloud data solutions in the context of business applications, cost optimization, client's strategic needs and future growth goals as it relates to becoming a 'data driven' organization.
- Applying and creating leading practices that support high availability, scalable, process and storage intensive solutions architectures to data integration/migration, analytics and insights, AI, and ML requirements.
- Applying leadership and review to create high quality detailed documentation related to cloud data Engineering.
- Implementing cloud data orchestration and data integration patterns (AWS Glue, Azure Data Factory, Event Hub, Databricks, etc.), storage and processing (Redshift, Azure Synapse, BigQuery, Snowflake)
- Possessing a certification(s) in one of the following is a big plus - AWS/Azure/GCP data engineering, and Migration.
- 10+ years’ experience as data engineer.
- Must have 5+ Years in implementing data engineering solutions with multiple cloud providers and toolsets.
- This is hands on role building data pipelines using Cloud Native and Partner Solutions. Hands-on technical experience with Data at Scale.
- Must have deep expertise in one of the programming languages for data processes (Python, Scala). Experience with Python, PySpark, Hadoop, Hive and/or Spark to write data pipelines and data processing layers.
- Must have worked with multiple database technologies and patterns. Good SQL experience for writing complex SQL transformation.
- Performance Tuning of Spark SQL running on S3/Data Lake/Delta Lake/ storage and Strong Knowledge on Databricks and Cluster Configurations.
- Nice to have Databricks administration including security and infrastructure features of Databricks.
- Experience with Development Tools for CI/CD, Unit and Integration testing, Automation and Orchestration
Mid / Senior Big Data Engineer
Role: Big Data EngineerNumber of open positions: 5Location: PuneAt Clairvoyant, we're building a thriving big data practice to help enterprises enable and accelerate the adoption of Big data and cloud services. In the big data space, we lead and serve as innovators, troubleshooters, and enablers. Big data practice at Clairvoyant, focuses on solving our customer's business problems by delivering products designed with best in class engineering practices and a commitment to keep the total cost of ownership to a minimum.
- 4-10 years of experience in software development.
- At least 2 years of relevant work experience on large scale Data applications.
- Strong coding experience in Java is mandatory
- Good aptitude, strong problem solving abilities, and analytical skills, ability to take ownership as appropriate
- Should be able to do coding, debugging, performance tuning and deploying the apps to Prod.
- Should have good working experience on
- o Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet)
- o Kafka
- o J2EE Frameworks (Spring/Hibernate/REST)
- o Spark Streaming or any other streaming technology.
- Strong coding experience in Java is mandatory
- Ability to work on the sprint stories to completion along with Unit test case coverage.
- Experience working in Agile Methodology
- Excellent communication and coordination skills
- Knowledgeable (and preferred hands on) - UNIX environments, different continuous integration tools.
- Must be able to integrate quickly into the team and work independently towards team goals
- Take the complete responsibility of the sprint stories' execution
- Be accountable for the delivery of the tasks in the defined timelines with good quality.
- Follow the processes for project execution and delivery.
- Follow agile methodology
- Work with the team lead closely and contribute to the smooth delivery of the project.
- Understand/define the architecture and discuss the pros-cons of the same with the team
- Involve in the brainstorming sessions and suggest improvements in the architecture/design.
- Work with other team leads to get the architecture/design reviewed.
- Work with the clients and counter-parts (in US) of the project.
- Keep all the stakeholders updated about the project/task status/risks/issues if there are any.
Experience: 4 to 9 years
Keywords: java, scala, spark, software development, hadoop, hive
Job Location: Chennai
The Engineering team is seeking a Data Architect. As a Data Architect, you will drive a
Data Architecture strategy across various Data Lake platforms. You will help develop
reference architecture and roadmaps to build highly available, scalable and distributed
data platforms using cloud based solutions to process high volume, high velocity and
wide variety of structured and unstructured data. This role is also responsible for driving
innovation, prototyping, and recommending solutions. Above all, you will influence how
users interact with Conde Nast’s industry-leading journalism.
Data Architect is responsible for
• Demonstrated technology and personal leadership experience in architecting,
designing, and building highly scalable solutions and products.
• Enterprise scale expertise in data management best practices such as data integration,
data security, data warehousing, metadata management and data quality.
• Extensive knowledge and experience in architecting modern data integration
frameworks, highly scalable distributed systems using open source and emerging data
• Experience building external cloud (e.g. GCP, AWS) data applications and capabilities is
• Expert ability to evaluate, prototype and recommend data solutions and vendor
technologies and platforms.
• Proven experience in relational, NoSQL, ELT/ETL technologies and in-memory
• Experience with DevOps, Continuous Integration and Continuous Delivery technologies
• This role requires 15+ years of data solution architecture, design and development
• Solid experience in Agile methodologies (Kanban and SCRUM)
• Very Strong Experience in building Large Scale High Performance Data Platforms.
• Passionate about technology and delivering solutions for difficult and intricate
problems. Current on Relational Databases and No sql databases on cloud.
• Proven leadership skills, demonstrated ability to mentor, influence and partner with
cross teams to deliver scalable robust solutions..
• Mastery of relational database, NoSQL, ETL (such as Informatica, Datastage etc) /ELT
and data integration technologies.
• Experience in any one of Object Oriented Programming (Java, Scala, Python) and
• Creative view of markets and technologies combined with a passion to create the
• Knowledge on cloud based Distributed/Hybrid data-warehousing solutions and Data
Lake knowledge is mandate.
• Good understanding of emerging technologies and its applications.
• Understanding of code versioning tools such as GitHub, SVN, CVS etc.
• Understanding of Hadoop Architecture and Hive SQL
• Knowledge in any one of the workflow orchestration
• Understanding of Agile framework and delivery
● Experience in AWS and EMR would be a plus
● Exposure in Workflow Orchestration like Airflow is a plus
● Exposure in any one of the NoSQL database would be a plus
● Experience in Databricks along with PySpark/Spark SQL would be a plus
● Experience with the Digital Media and Publishing domain would be a
● Understanding of Digital web events, ad streams, context models
About Condé Nast
CONDÉ NAST INDIA (DATA)
Over the years, Condé Nast successfully expanded and diversified into digital, TV, and social
platforms - in other words, a staggering amount of user data. Condé Nast made the right
move to invest heavily in understanding this data and formed a whole new Data team
entirely dedicated to data processing, engineering, analytics, and visualization. This team
helps drive engagement, fuel process innovation, further content enrichment, and increase
market revenue. The Data team aimed to create a company culture where data was the
common language and facilitate an environment where insights shared in real-time could
The Global Data team operates out of Los Angeles, New York, Chennai, and London. The
team at Condé Nast Chennai works extensively with data to amplify its brands' digital
capabilities and boost online revenue. We are broadly divided into four groups, Data
Intelligence, Data Engineering, Data Science, and Operations (including Product and
Marketing Ops, Client Services) along with Data Strategy and monetization. The teams built
capabilities and products to create data-driven solutions for better audience engagement.
What we look forward to:
We want to welcome bright, new minds into our midst and work together to create diverse
forms of self-expression. At Condé Nast, we encourage the imaginative and celebrate the
extraordinary. We are a media company for the future, with a remarkable past. We are
Condé Nast, and It Starts Here.
Ideal candidates should have technical experience in migrations and the ability to help customers get value from Datametica's tools and accelerators.
Experience : 7+ years
Location : Pune / Hyderabad
- Drive and participate in requirements gathering workshops, estimation discussions, design meetings and status review meetings
- Participate and contribute in Solution Design and Solution Architecture for implementing Big Data Projects on-premise and on cloud
- Technical Hands on experience in design, coding, development and managing Large Hadoop implementation
- Proficient in SQL, Hive, PIG, Spark SQL, Shell Scripting, Kafka, Flume, Scoop with large Big Data and Data Warehousing projects with either Java, Python or Scala based Hadoop programming background
- Proficient with various development methodologies like waterfall, agile/scrum and iterative
- Good Interpersonal skills and excellent communication skills for US and UK based clients
A global Leader in the Data Warehouse Migration and Modernization to the Cloud, we empower businesses by migrating their Data/Workload/ETL/Analytics to the Cloud by leveraging Automation.
We have expertise in transforming legacy Teradata, Oracle, Hadoop, Netezza, Vertica, Greenplum along with ETLs like Informatica, Datastage, AbInitio & others, to cloud-based data warehousing with other capabilities in data engineering, advanced analytics solutions, data management, data lake and cloud optimization.
Datametica is a key partner of the major cloud service providers - Google, Microsoft, Amazon, Snowflake.
We have our own products!
Eagle – Data warehouse Assessment & Migration Planning Product
Raven – Automated Workload Conversion Product
Pelican - Automated Data Validation Product, which helps automate and accelerate data migration to the cloud.
Why join us!
Datametica is a place to innovate, bring new ideas to live and learn new things. We believe in building a culture of innovation, growth and belonging. Our people and their dedication over these years are the key factors in achieving our success.
Benefits we Provide!
Working with Highly Technical and Passionate, mission-driven people
Subsidized Meals & Snacks
Access to various learning tools and programs
Certification Reimbursement Policy
Check out more about us on our website below!
Should have Passion to learn and adapt new technologies, understanding,
solving/troubleshooting issues and risks, able to make informed decisions and ability to
lead the projects.
- 2-5 Years’ Experience with functional programming
- Experience with functional programming using Scala with Spark framework.
- Strong understanding of Object-oriented programming, data structures and algorithms
- Good experience in any of the cloud platforms (Azure, AWS, GCP) etc.,
- Experience with distributed (multi-tiered) systems, relational databases and NoSql storage solutions
- Desire to learn new technologies and languages
- Participation in software design, development, and code reviews
- High level of proficiency with Computer Science/Software Engineering knowledge and contribution to the technical skills growth of other team members
- Design, build and configure applications to meet business process and application requirements
- Proactively identify and communicate potential issues and concerns and recommend/implement alternative solutions as appropriate.
- Troubleshooting & Optimization of existing solution
Provide advice on technical design to ensure solutions are forward looking and flexible for potential future requirements and business needs.
(Hadoop, HDFS, Kafka, Spark, Hive)
Overall Experience - 8 to 12 years
Relevant exp on Big data - 3+ years in above
Salary: Max up-to 20LPA
Job location - Chennai / Bangalore /
Notice Period - Immediate joiner / 15-to-20-day Max
The Responsibilities of The Senior Data Engineer Are:
- Requirements gathering and assessment
- Breakdown complexity and translate requirements to specification artifacts and story boards to build towards, using a test-driven approach
- Engineer scalable data pipelines using big data technologies including but not limited to Hadoop, HDFS, Kafka, HBase, Elastic
- Implement the pipelines using execution frameworks including but not limited to MapReduce, Spark, Hive, using Java/Scala/Python for application design.
- Mentoring juniors in a dynamic team setting
- Manage stakeholders with proactive communication upholding TheDataTeam's brand and values
A Candidate Must Have the Following Skills:
- Strong problem-solving ability
- Excellent software design and implementation ability
- Exposure and commitment to agile methodologies
- Detail oriented with willingness to proactively own software tasks as well as management tasks, and see them to completion with minimal guidance
- Minimum 8 years of experience
- Should have experience in full life-cycle of one big data application
- Strong understanding of various storage formats (ORC/Parquet/Avro)
- Should have hands on experience in one of the Hadoop distributions (Hortoworks/Cloudera/MapR)
- Experience in at least one cloud environment (GCP/AWS/Azure)
- Should be well versed with at least one database (MySQL/Oracle/MongoDB/Postgres)
- Bachelor's in Computer Science, and preferably, a Masters as well - Should have good code review and debugging skills
Additional skills (Good to have):
- Experience in Containerization (docker/Heroku)
- Exposure to microservices
- Exposure to DevOps practices - Experience in Performance tuning of big data applications
- Must have 5-8 years of experience in handling data
- Must have the ability to interpret large amounts of data and to multi-task
- Must have strong knowledge of and experience with programming (Python), Linux/Bash scripting, databases(SQL, etc)
- Must have strong analytical and critical thinking to resolve business problems using data and tech
- Must have domain familiarity and interest of – Cloud technologies (GCP/Azure Microsoft/ AWS Amazon), open-source technologies, Enterprise technologies
- Must have the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Must have good communication skills
- Working knowledge/exposure to ElasticSearch, PostgreSQL, Athena, PrestoDB, Jupyter Notebook