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We are looking for a Marketing Lead to own demand generation, AI search visibility, and the content engine that feeds both. The ideal candidate will own: account-based marketing and marketing analytics.

Key Responsibilities

• Run personalized ABM campaigns and own MQLs.
• Set up conversion tracking, attribution and funnel reporting.
• Own AI-search visibility for priority keywords across LLMs.
• Run the content engine for social media and website.
• Plan and run paid ad campaigns and track performance.

Qualifications

• Bachelor’s or Master’s degree; MBA in Marketing preferred.
• 7+ years in B2B marketing.
• Hands-on ABM or target-account campaign experience
• Hands-on LinkedIn Ads experience with budget accountability.
• Strong business writing and editing in English.

Preferred Skills

• Marketing experience in healthcare, or data and AI solutions.
• Exposure to Generative AI tools in a marketing workflow.
• Practical GA4 and Google Search Console skill.
• Ability to plan and execute webinar and events.
• Working knowledge of AEO/GEO.

Perks

• Flexible Timings
• 5 Days Working
• Healthy Environment
• Celebration
• Learn and Grow
• Build the Community
• Medical Insurance Benefit

We are looking for a highly skilled Senior Data Engineer with strong experience in modern data engineering and cloud data platforms. The ideal candidate will have hands-on experience with Snowflake or Databricks, along with a strong understanding of data engineering, ETL/ELT processes, data modelling, data warehousing, and cloud platforms.
Hands-on experience with at least one of Snowflake or Databricks is mandatory, while working knowledge of the other platform is good to have. The candidate will be responsible for designing, developing, optimizing, and maintaining scalable data pipelines and data solutions.
The role will involve working closely with data engineers, data scientists, analysts, and business teams to deliver reliable and high-quality data solutions.

Key Responsibilities:

Data Architecture & Development: Design, develop, and optimize scalable, secure, and high-performance data solutions using Snowflake and/or Databricks.
ETL/ELT Pipeline Engineering: Build and maintain robust data pipelines with appropriate orchestration, monitoring, retries, logging, and error handling.
Data Modelling & Transformation: Develop scalable data models and transformations following data warehousing and lakehouse best practices.
Snowflake / Databricks Development: Develop and maintain data solutions using Snowflake or Databricks and optimize data processing and query performance.
Advanced Data Engineering & Optimization: Develop and optimize complex SQL and PySpark transformations for large-scale batch and incremental processing. Implement CDC, merge/upsert patterns, partitioning, and schema evolution while performing hands-on tuning of Snowflake queries, Spark jobs, and Delta Lake workloads. Build pipeline observability through execution logging, source-to-target reconciliation, data completeness checks, error diagnostics, and automated failure handling.
Data Quality: Implement data validation, automated testing, monitoring, and quality frameworks to ensure data integrity and reliability.
Performance Optimization: Monitor pipeline and job performance, troubleshoot issues, and optimize queries and data processing workloads.
Cloud Data Engineering: Develop and manage data pipelines and solutions on AWS, Azure, or GCP.
Collaboration: Work with data analysts, data scientists, and business stakeholders to translate requirements into technical specifications and deliverables.
Technical Contribution: Participate in code reviews, technical discussions, design reviews, and establish data engineering best practices.
Innovation & Research: Stay updated on advancements in Snowflake, Databricks, cloud data platforms, AI/ML, and modern data engineering practices.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
• 5+ years of experience in data engineering, with hands-on experience in at least one of Snowflake or Databricks.
• Strong understanding of:
  • Data modelling
  • Data warehousing
  • ETL/ELT processes
  • Data Lake / Lakehouse architectures
  • Data quality and validation
• Snowflake: Hands-on experience with data modelling, query/performance optimization, access control, streams, tasks, external tables, or equivalent capabilities.
• Databricks: Hands-on experience with data engineering, Spark, Delta Lake/Lakehouse concepts, and data pipeline development.
• Snowflake or Databricks – one must be hands-on; knowledge of the other is good to have.
  Proficiency in SQL and Python. Spark experience is expected for candidates with Databricks exposure.
• Experience building data pipelines on cloud platforms such as AWS, Azure, or GCP.
• Experience with orchestration tools such as Apache Airflow, Azure Data Factory, AWS Glue, or equivalent.
• Familiarity with dbt and modern ELT practices is good to have.
  Familiarity with Git and CI/CD practices.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently as well as collaboratively in a team environment.

Preferred Skills:

• Hands-on experience with both Snowflake and Databricks.
• Experience with Apache Airflow and dbt.
• Experience with streaming data pipelines such as Kafka, Kinesis, or Pub/Sub.
• Exposure to Generative AI, ML, or advanced analytics solutions.
• Familiarity with BI/analytics tools such as Power BI, Tableau, or Looker.
• Knowledge of data governance, security, and compliance best practices.
• Familiarity with Terraform or other infrastructure-as-code tools.
• Exposure to multiple cloud platforms such as AWS, Azure, or GCP.

Perks

• Flexible Timings
• 5 Days Working
• Healthy Environment
• Celebration
• Learn and Grow
• Build the Community
• Medical Insurance Benefit

We are seeking an accomplished Lead Data Engineer with strong expertise in modern cloud data platforms, with hands-on experience in Snowflake or Databricks. The ideal candidate will be responsible for designing, developing, and optimizing scalable data solutions, building robust data pipelines, and ensuring data quality, reliability, and performance.
The candidate should have strong experience in data engineering, data modelling, ETL/ELT processes, and cloud data platforms, with the ability to work across Snowflake and Databricks. Hands-on experience with at least one of these platforms is mandatory, while working knowledge of the other is good to have.
This role also involves providing technical leadership, mentoring engineers, collaborating with cross-functional teams, and translating business requirements into scalable technical solutions.

Key Responsibilities:

Data Architecture & Development: Lead the design, development, and optimization of scalable, secure, and high-performance data solutions using Snowflake and/or Databricks.
ETL/ELT Pipeline Engineering: Design, build, and maintain robust data pipelines using appropriate orchestration and data engineering frameworks, ensuring reliability, scalability, monitoring, retries, and error handling.
Data Modelling & Transformation: Develop scalable data models and transformations following best practices for data warehousing and modern lakehouse architectures.
Snowflake / Databricks Development: Develop and optimize data solutions on Snowflake or Databricks, including performance tuning, data processing, storage optimization, and workload management.
Data Quality & Governance: Implement data validation, automated testing, monitoring, governance, and security practices to ensure data integrity, reliability, and compliance.
Performance Optimization: Identify and resolve performance bottlenecks across data pipelines, queries, jobs, and data processing workloads.
Cloud Data Engineering: Build and manage data solutions on cloud platforms such as AWS, Azure, or GCP.
Collaboration: Partner with data analysts, data scientists, architects, and business stakeholders to translate requirements into scalable technical solutions.
Technical Leadership: Provide technical guidance and mentorship to data engineers, conduct code/design reviews, and establish engineering best practices.
Innovation & Research: Stay current with advancements in cloud data platforms, data engineering, analytics, and AI/ML technologies and recommend relevant improvements.
Infrastructure & CI/CD: Work with version control, CI/CD, and infrastructure-as-code practices for reliable deployment and management of data platforms.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
• 7–10 years of experience in data engineering, with strong hands-on experience in at least one of Snowflake or Databricks.
• Demonstrated experience in leading and mentoring data engineering teams.
• Strong working knowledge of modern data engineering concepts, including:
  • Data modelling and data warehousing
  • ETL/ELT processes
  • Data Lake / Lakehouse architectures
  • Batch and incremental data processing
  • Data quality and validation
• Snowflake: Strong hands-on experience in data modelling, performance tuning, access control, and features such as streams, tasks, external tables, or equivalent capabilities.
• Databricks: Strong hands-on experience with data engineering, Spark-based processing, Delta Lake/Lakehouse concepts, and pipeline development.
• Snowflake or Databricks – one must be hands-on; knowledge of the other is good to have.
• Proficiency in SQL and Python.
• Spark experience is expected for candidates with Databricks exposure.
• Experience building and managing data pipelines on AWS, Azure, or GCP.
• Experience with data orchestration tools such as Apache Airflow, Azure Data Factory, AWS Glue, or equivalent.
• Familiarity with transformation frameworks such as dbt is good to have.
• Familiarity with version control systems such as Git and CI/CD practices.
• Exposure to infrastructure-as-code tools such as Terraform is good to have.
• Strong analytical, problem-solving, collaboration, and communication skills.
• Demonstrated ability to lead technical projects and mentor junior/mid-level engineers.

Preferred Skills:

• Hands-on experience with both Snowflake and Databricks.
• Experience with dbt and Apache Airflow.
• Experience with streaming technologies such as Kafka, Kinesis, or Pub/Sub.
• Experience with Generative AI, ML, or advanced analytics applications.
• Familiarity with BI/analytics tools such as Power BI, Tableau, Looker, or similar.
• Knowledge of data governance, security, and compliance frameworks.
• Experience with multiple cloud platforms such as AWS, Azure, or GCP.

Perks

• Flexible Timings
• 5 Days Working
• Healthy Environment
• Celebration
• Learn and Grow
• Build the Community
• Medical Insurance Benefit

We are looking for a Digital Marketing Intern to support our SEO, and social media work.

Key Responsibilities

• Track daily site health and search performance, and flag issues.
• Publish and optimize website and blog content.
• Run keyword and prompt research and turn it into briefs for the content team.
• Maintain directory and profile listings, and compile backlink data.

Qualifications

• Bachelor’s degree; MBA in Marketing preferred. Fresh graduates are encouraged to apply.
• Strong written English and careful attention to detail.
• Comfortable in spreadsheets .
• Exposure to AI tools for research and content workflows.

Preferred Skills

• Basic understanding of digital marketing.
• Familiarity with any CMS, GSC, GA4 (Good to have)
• Interest in B2B, data and AI, or healthcare technology.

Perks

• Flexible Timings
• 5 Days Working
• Healthy Environment
• Celebration
• Learn and Grow
• Build the Community
• Medical Insurance Benefit