Content Writer

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:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments

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.

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.

Job Title: AI/ML Engineer

Expereince: 5+ Years

Location: Remote

Responsbilities

Algorithm Development:

• Design and develop cutting-edge algorithms for solving complex business problems.

• Collaborate with cross-functional teams to understand business requirements and translate them into effective AI/ML solutions.

Content Customization:

• Implement content customization strategies to enhance user experience and engagement.

• Work closely with stakeholders to tailor AI/ML models for specific business needs.

Data Collection and Preprocessing:

• Develop robust data collection strategies to ensure the availability of high-quality datasets.

• Implement preprocessing techniques to clean and prepare data for model training.

Model Training and Evaluation:

• Utilize machine learning frameworks such as TensorFlow, Pytorch, and Scikit Learn for model training.

• Conduct rigorous evaluation of models to ensure accuracy and reliability.

Monitoring and Optimization:

• Implement monitoring systems to track the performance of deployed models.

• Continuously optimize models for better efficiency and accuracy.

Data Analytics and Reporting:

• Leverage statistical modelling techniques to derive meaningful insights from data.

• Generate reports and dashboards to communicate findings to stakeholders.

Documentation:

• Create comprehensive documentation for algorithms, models, and implementation details.

• Provide documentation for training, deployment, and maintenance procedures.

Skills:

• 6+ years of experience in AI/ML engineering.
• Proficiency in Python and machine learning frameworks (TensorFlow, Pytorch, Scikit Learn).
• Experience in Natural Language Processing (NLP) and Computer Vision.
• Expertise in Generative AI techniques.
• Familiarity with cloud platforms such as Azure and AWS.
• Strong background in statistical modelling and content customization.
• Excellent problem-solving skills and ability to work independently.
• Strong communication and collaboration skills

• 2+ years of experience in Technical recruitment
• Design and implement overall recruiting strategy 
• Develop and update job descriptions and job specifications 
• Perform job and task analysis to document job requirements and objectives 
• Source and recruit candidates by using databases, social media etc 
• Screen candidates resumes and job applications 
• Conduct interviews using various reliable recruiting and selection tools/methods to filter candidates within schedule 
• Assess applicants’ https://resources.workable.com/tutorial/recruiting-skills-training" target="_blank">relevant knowledge, skills, soft skills, experience and aptitudes 
• Onboard new employees in order to become fully integrated 
• Monitor and apply HR recruiting best practices 
• Provide analytical and well documented recruiting reports to the rest of the team 
• Act as a point of contact and build influential candidate relationships during the selection process 

• Proficient in Java, Node or Python
• Experience with NewRelic, Splunk, SignalFx, DataDog etc.
• Monitoring and alerting experience
• Full stack development experience
• Hands-on with building and deploying micro services in Cloud (AWS/Azure)
• Experience with terraform w.r.t Infrastructure As Code
• Should have experience troubleshooting live production systems using monitoring/log analytics tools
• Should have experience leading a team (2 or more engineers)
• Experienced using Jenkins or similar deployment pipeline tools
• Understanding of distributed architectures