Ab>initio, Big Data, Informatica, Tableau, Data Architect, Cognos, Microstrategy, Healther Business Analysts, Cloud etc.
at Exusia

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Company Description
TECHSOPHY specializes in productizing solutions based on new technology, focusing on emerging platforms of BPM & ECM, Low Code, AI (ML/RPA/NLP). Founded in 2009, TECHSOPHY operates with headquarters in California, USA, and regional offices in Dubai, UAE, and an offshore innovation center in Hyderabad, India.
Qualifications
- Solid Fundamentals and exceptional problem-solving skills
- Solid and fluent understanding of algorithms and data structures
- Proficiency in Scala + Spark
- Proficiency in Scala + Play framework
- Experience Range: 4 to 7 Years
Requirement:
Some or all of them – because we believe intelligent people can pick up whatever they need in a short period of time. You just need to prove that you can:
- Excellent programming skills and knowledge of Java / Scala
- Excellent software design, problem-solving, and debugging skills
- Experience with modern Big Data technologies such as Spark, NoSQL, Cassandra, Kafka, MapReduce, and the Hadoop ecosystem is a must-have
- Experience with data analytics and the ability to mine data to obtain insights are much appreciated
Review Criteria
- Strong Dremio / Lakehouse Data Architect profile
- 5+ years of experience in Data Architecture / Data Engineering, with minimum 3+ years hands-on in Dremio
- Strong expertise in SQL optimization, data modeling, query performance tuning, and designing analytical schemas for large-scale systems
- Deep experience with cloud object storage (S3 / ADLS / GCS) and file formats such as Parquet, Delta, Iceberg along with distributed query planning concepts
- Hands-on experience integrating data via APIs, JDBC, Delta/Parquet, object storage, and coordinating with data engineering pipelines (Airflow, DBT, Kafka, Spark, etc.)
- Proven experience designing and implementing lakehouse architecture including ingestion, curation, semantic modeling, reflections/caching optimization, and enabling governed analytics
- Strong understanding of data governance, lineage, RBAC-based access control, and enterprise security best practices
- Excellent communication skills with ability to work closely with BI, data science, and engineering teams; strong documentation discipline
- Candidates must come from enterprise data modernization, cloud-native, or analytics-driven companies
Preferred
- Preferred (Nice-to-have) – Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments
Job Specific Criteria
- CV Attachment is mandatory
- How many years of experience you have with Dremio?
- Which is your preferred job location (Mumbai / Bengaluru / Hyderabad / Gurgaon)?
- Are you okay with 3 Days WFO?
- Virtual Interview requires video to be on, are you okay with it?
Role & Responsibilities
You will be responsible for architecting, implementing, and optimizing Dremio-based data lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.
- Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
- Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
- Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
- Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
- Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
- Support self-service analytics by enabling governed data products and semantic layers.
- Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
- Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.
Ideal Candidate
- Bachelor’s or master’s in computer science, Information Systems, or related field.
- 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
- Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
- Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
- Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
- Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
- Excellent problem-solving, documentation, and stakeholder communication skills.
ROLES AND RESPONSIBILITIES:
You will be responsible for architecting, implementing, and optimizing Dremio-based data Lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.
- Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
- Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
- Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
- Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
- Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
- Support self-service analytics by enabling governed data products and semantic layers.
- Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
- Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.
IDEAL CANDIDATE:
- Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
- 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
- Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
- Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
- Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
- Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
- Excellent problem-solving, documentation, and stakeholder communication skills.
PREFERRED:
- Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
- Exposure to Snowflake, Databricks, or BigQuery environments.
- Experience in high-tech, manufacturing, or enterprise data modernization programs.
Solid Fundamentals and exceptional problem-solving skills
Solid and fluent understanding of algorithm and data structures
Proficiency in Scala + Spark
Experience Range: 3 to 7 Years
Requirement Some or all of them – because we believe intelligent people can pick up whatever they need in a short period of time. You just need to prove that you can:
Excellent programming skills and knowledge of Java / Scala
Excellent software design, problem solving and debugging skills
Experience with modern Big data technologies such as Spark, NoSQL, Cassandra, Kafka, Map Reduce, Hadoop ecosystem is a must have
Experience with data analytics and ability to mine data to obtain insights is much appreciated
We are looking for a Business Intelligence (BI)/Data Analyst to create and manage Power Bl and analytics solutions that turn data into knowledge. In this role, you should have a background in data and business analysis. If you are self-directed, passionate about data,
and have business acumen and problem-solving aptitude, we'd like to meet you. Ultimately, you will enhance our business intelligence system to help us make better decisions.
Requirements and Qualifications
- BSc/BA in Computer Science, Engineering, or relevant field.
- Financial experience and Marketing background is a plus
- Strong Power BI development skills including Migration of existing deliverables to PowerBl.
- Ability to work autonomously
- Data modelling, Calculations, Conversions, Scheduling Data refreshes in Power-BI.
- Proven experience as a Power BI Developer is a must.
- Industry experience is preferred. Familiarity with other BI tools (Tableau, QlikView).
- Analytical mind with a problem-solving aptitude.
Responsibilities
- Design, develop and maintain business intelligence solutions
- Craft and execute queries upon request for data
- Present information through reports and visualization based on requirements gathered from stakeholders
- Interact with the team to gain an understanding of the business environment, technical context, and organizational strategic direction
- Design, build and deploy new, and extend existing dashboards and reports that synthesize distributed data sources
- Ensure data accuracy, performance, usability, and functionality requirements of BI platform
- Manage data through MS Excel, Google sheets, and SQL applications, as required and support other analytics platforms
- Develop and execute database queries and conduct analyses
- Develop and update technical documentation requirements
- Communicate insights to both technical and non-technical audiences.
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.
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/">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">https://www.slintel.com/slintel
Linkedin (6sense) : https://www.linkedin.com/company/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/">https://6sense.com/
Acquisition News :
https://inc42.com/buzz/us-based-based-6sense-acquires-b2b-buyer-intelligence-startup-slintel/
Funding Details & News :
Slintel funding : https://www.crunchbase.com/organization/slintel">https://www.crunchbase.com/organization/slintel
6sense funding : https://www.crunchbase.com/organization/6sense">https://www.crunchbase.com/organization/6sense
https://www.nasdaq.com/articles/ai-software-firm-6sense-valued-at-%245.2-bln-after-softbank-joins-funding-round">https://www.nasdaq.com/articles/ai-software-firm-6sense-valued-at-%245.2-bln-after-softbank-joins-funding-round
https://www.bloomberg.com/news/articles/2022-01-20/6sense-reaches-5-2-billion-value-with-softbank-joining-round">https://www.bloomberg.com/news/articles/2022-01-20/6sense-reaches-5-2-billion-value-with-softbank-joining-round
https://xipometer.com/en/company/6sense">https://xipometer.com/en/company/6sense
Slintel & 6sense Customers :
https://www.featuredcustomers.com/vendor/slintel/customers
https://www.featuredcustomers.com/vendor/6sense/customers">https://www.featuredcustomers.com/vendor/6sense/customers
About the job
Responsibilities
- 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
Requirements
- 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
Job Description
- Solid technical skills with a proven and successful history working with data at scale and empowering organizations through data
- Big data processing frameworks: Spark, Scala, Hadoop, Hive, Kafka, EMR with Python
- Advanced experience and hands-on architecture and administration experience on big data platforms
• Work with various stakeholders, understand requirements, and build solutions/data pipelines
that address the needs at scale
• Bring key workloads to the clients’ Snowflake environment using scalable, reusable data
ingestion and processing frameworks to transform a variety of datasets
• Apply best practices for Snowflake architecture, ELT and data models
Skills - 50% of below:
• A passion for all things data; understanding how to work with it at scale, and more importantly,
knowing how to get the most out of it
• Good understanding of native Snowflake capabilities like data ingestion, data sharing, zero-copy
cloning, tasks, Snowpipe etc
• Expertise in data modeling, with a good understanding of modeling approaches like Star
schema and/or Data Vault
• Experience in automating deployments
• Experience writing code in Python, Scala or Java or PHP
• Experience in ETL/ELT either via a code-first approach or using low-code tools like AWS Glue,
Appflow, Informatica, Talend, Matillion, Fivetran etc
• Experience in one or more of the AWS especially in relation to integration with Snowflake
• Familiarity with data visualization tools like Tableau or PowerBI or Domo or any similar tool
• Experience with Data Virtualization tools like Trino, Starburst, Denodo, Data Virtuality, Dremio
etc.
• Certified SnowPro Advanced: Data Engineer is a must.










