Qureos Mentor

JP Techno Park

Job Title: &ensp;&ensp;&ensp;&ensp;&ensp;Tech Lead Data Engineering (DBT)Location: &ensp;&ensp;&ensp;&ensp; Chennai (On-Site)Experience: &ensp;&ensp;&ensp;7+ YearsPosition Type: Full-TimeShift Timings: 2 - 11 PMSkillset: &ensp;&ensp;&ensp;&ensp;&ensp; Data Engineering, ETL Pipelines, DBT (Data Build Tool / Data Built Tool), Python, SQLAbout the Role: We are seeking an experienced Data Engineering Lead (DBT Tech Lead) to design, build, and lead scalable data transformation and pipeline solutions within a modern data stack environment. The ideal candidate will have deep experience in ETL and Data Engineering with recent hands-on expertise in DBT (Data Build Tool) for data modeling, orchestration, and transformation. This role requires a strong command of SQL, data pipeline optimization, and the ability to lead end-to-end data initiatives that power analytics and business intelligence platforms.Key Responsibilities<ul><li>Lead the design, development, and maintenance of data pipelines and ETL workflows.</li><li>Build, optimize, and manage data transformation models using DBT (Cloud or Core).</li><li>Collaborate with data architects and analysts to define data models, schemas, and lineage.</li><li>Ensure high-quality data delivery by implementing best practices for testing, versioning, and documentation within DBT.</li><li>Work with modern data warehouses (e.g., Snowflake, BigQuery, Redshift, Databricks) for transformation and analytics.</li><li>Drive continuous improvement in data architecture, performance tuning, and data governance.</li><li>Provide technical leadership, mentorship, and guidance to junior data engineers.</li><li>Partner with cross-functional teams to translate business requirements into scalable data solutions.</li></ul>Required Skills &amp; Experience<ul><li>8+ years of experience in Data Engineering, ETL, and pipeline development.</li><li>2+ years of recent hands-on experience with DBT (Data Build Tool) for transformation and modeling.</li><li>Strong proficiency in SQL (advanced query optimization, data modeling, performance tuning).</li><li>Hands-on experience with at least one modern cloud data warehouse (Snowflake, BigQuery, Redshift, Databricks).</li><li>Proficiency with data pipeline orchestration tools (Airflow, Prefect, or similar).</li><li>Understanding of data warehousing concepts, data quality frameworks, and modern data stack.</li><li>Strong analytical, problem-solving, and troubleshooting skills.</li><li>Excellent communication and team collaboration abilities.</li></ul>Nice to Have<ul><li>Experience with Python or Spark for advanced data processing.</li><li>Exposure to data observability tools (e.g., Great Expectations, Monte Carlo).</li><li>Knowledge of Git-based CI/CD workflows for DBT deployment.</li></ul>Job Type: Full-timePay: &#8377;2,500,000.00 - &#8377;3,000,000.00 per yearExperience:<ul><li>Lead Data Engineering: 10 years (Required)</li><li>DBT: 10 years (Required)</li><li>Data Build Tool: 10 years (Required)</li><li>DBT Lead: 10 years (Required)</li><li>ETL: 10 years (Required)</li><li>Pipeline Development: 10 years (Required)</li><li>SQL: 10 years (Required)</li><li>Data warehouse: 10 years (Required)</li><li>Snowflake: 10 years (Required)</li><li>BigQuery: 10 years (Required)</li><li>Redshift: 10 years (Required)</li><li>Data pipeline orchestration: 10 years (Required)</li><li>Airflow: 10 years (Required)</li><li>Python : 10 years (Required)</li><li>Data observability: 10 years (Required)</li></ul>Work Location: In person

Tech Lead Data Engineering (DBT)

<ul><li>JOB DESCRIPTION</li></ul>We are seeking a highly skilled Data Scientist along with strong Data Engineering expertise to join Advance Analytics and Modeling team. The ideal candidate will have a proven ability to work with diverse datasets, build machine learning models, and deploy scalable solutions. This role requires proficiency in Python, advanced analytical skills, and experience in developing machine learning models and dashboards in python. The candidate should have experience in deploying machine learning models in production using cloud platforms such as AWS or Azure and workflow orchestration tools like Airflow.Key Responsibilities:<ul><li>Develop and deploy machine learning models for classification, regression, and</li><li>clustering problems.</li><li>Perform statistical analysis to derive actionable insights from data.</li></ul><ul><li>Design and implement predictive analytics solutions to support business decision-</li></ul>making.Docker)translate them into analytical solutions.<ul><li>Design, build, and optimize data pipelines using Airflow.</li><li>Ensure data quality, integrity, and availability through robust ETL processes.</li><li>Work on model deployment using Python-based frameworks and containerization (e.g.,</li><li>Create interactive dashboards using Python libraries to visualize data and results.</li><li>Collaborate with cross functional teams to understand business requirements and</li></ul>Required Skills &amp; Expertise:Technical Skills:<ul><li>Proficiency in Python, advanced Python concepts (object-oriented programming,</li><li>multi-threading, etc.), SQL and Excel.</li><li>Hands-on experience with data visualization tools (e.g., Tableau, Power BI) is a</li></ul>plus.Analytics and Machine Learning:<ul><li>Strong analytical skills and experience in predictive modeling.</li><li>Hands-on experience with machine learning libraries like scikit-learn, TensorFlow</li><li>or PyTorch.</li><li>Ability to work with large datasets and extract meaningful insights to generate</li></ul>output<ul><li>Ability to work on ad-hoc requests to support business needs and derive</li></ul>actionable insightsData Visualization:Streamlit.<ul><li>Experience inn creating dashboards using Python libraries like Plotly, Dash, or</li></ul>Data Engineering:<ul><li>Knowledge of Airflow or similar workflow orchestration tools.</li><li>Expertise in ETL processes and pipeline automation.Model Deployment:</li><li>Familiarity with deploying machine learning models in production using Flask,</li><li>FastAPI, or similar frameworks.</li><li>Experience with containerization and orchestration tools (Docker, Kubernetes.)</li></ul>Tools and Platforms:<ul><li>Experience with version control tools like Git.</li><li>Familiarity with cloud platforms like AWS, Azure, or GCP is a plus.</li><li>Problem-Solving &amp; Communication: Strong problem-solving skills, with the ability to translate complex analytical findings into clear and actionable recommendations.</li><li>Excellent communication and presentation skills, with experience delivering</li><li>insights to senior stakeholders.Candidate Profile:</li><li>Educational Background: Bachelor&rsquo;s/Master&rsquo;s degree in Analytics, Data Science, Economics, Statistics, Engineering, or a related field.</li><li>Professional Experience: At least 5 years of experience in Data Science and Data</li></ul>Engineering.Job Type: Full-timePay: &#8377;1,500,000.00 - &#8377;1,800,000.00 per yearExperience:<ul><li>Data Scientist: 10 years (Required)</li><li>Python: 10 years (Required)</li><li>Analytical Data: 10 years (Required)</li><li>PySpark: 10 years (Required)</li><li>SQL: 10 years (Required)</li><li>Excel: 10 years (Required)</li><li>Data Visualization: 10 years (Required)</li><li>Insurance: 10 years (Required)</li><li>Tableau: 10 years (Required)</li><li>Power BI: 10 years (Required)</li><li>Data Engineering: 10 years (Required)</li><li>machine Learning: 10 years (Required)</li><li>ETL: 10 years (Required)</li><li>Automation: 10 years (Required)</li><li>Flask: 10 years (Required)</li></ul>Work Location: In person

Lead Analytical Data Scientist

Gen AI- B2/ C1 Must Have Skillsets:Data Science Machine Learning Gen AICommunication skills and job stability is mandatory criteria for selection. Experience 5 years at least and preferably tier 1 &amp; 2 colleges.Required Skills:1) Transformer models either fine-tuning or training on open source Transformer based model.build and fine tuning large scale language model using pytorch .2) Should have done projects on LLM Rag Gen Ai3) hands on experience on python coding.4) should have done Gen Ai project5)Machine learning or Deep learning any One is mandatory6) Excellent communication and Stakeholder management abilities.Job Type: Full-timePay: &#8377;2,000,000.00 - &#8377;2,100,000.00 per yearExperience:<ul><li>GenAI Data Scientist: 10 years (Required)</li><li>Data Science: 10 years (Required)</li><li>Machine Learning: 10 years (Required)</li><li>GenAI: 10 years (Required)</li><li>LLM: 10 years (Required)</li><li>Python: 10 years (Required)</li><li>PyTorch: 10 years (Required)</li></ul>Work Location: In person

GenAI Data Scientist

Join JP Techno Park and explore 3   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

JP Techno Park

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Tech Lead Data Engineering (DBT)

Lead Analytical Data Scientist

GenAI Data Scientist