Data Engineer at Hammoq · Remote, Indore, Ujjain, Hyderabad, Bengaluru (Bangalore) · 5 - 8 years · ₹5L - ₹15L / yr (ESOP available) · Raised funding · Remote friendly · Posted 15 Sep 2021
- Does analytics to extract insights from raw historical data of the organization.
- Generates usable training dataset for any/all MV projects with the help of Annotators, if needed.
- Analyses user trends, and identifies their biggest bottlenecks in Hammoq Workflow.
- Tests the short/long term impact of productized MV models on those trends.
- Skills - Numpy, Pandas, SPARK, APACHE SPARK, PYSPARK, ETL mandatory.

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Job Summary
We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.
Technical Skills
- Strong hands-on experience in Python and PySpark development.
- Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
- Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
- Experience with Power BI Data Modeling and Semantic Layer development.
- Proficiency in DAX (Data Analysis Expressions).
- Experience designing and managing Semantic Models in Power BI.
- Strong SQL skills and experience working with large datasets.
- Knowledge of data warehousing concepts and best practices.
Preferred Skills
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Exposure to modern data platforms like Databricks.
- Understanding of data governance and data quality frameworks.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
9+yrs
Bangalore/Hyderabad
immediate to 15days.
About Us
Corporate Web Solutions works on technology-driven digital solutions involving data, automation, web technologies, and artificial intelligence. Our internship programs focus on practical learning and real-world project exposure.
Role Overview
As a Data Science Intern, you'll work with datasets to perform analysis, visualization, and machine learning tasks while learning modern AI-assisted workflows.
Key Responsibilities
- Collect, clean, and analyze datasets.
- Perform exploratory data analysis.
- Create data visualizations and reports.
- Assist in developing machine learning models.
- Work with Python-based data science tools.
- Explore AI tools for data analysis and productivity.
Requirements
- Basic knowledge of Python.
- Understanding of data analysis fundamentals.
- Familiarity with Pandas and NumPy is a plus.
- Basic understanding of statistics.
- Analytical and problem-solving skills.
Perks
- Certificate of Internship
- Flexible work hours
- Mentorship and real project exposure
- Potential for PPO
- Letter of Recommendation
- Performance-Based Stipend available up to ₹18,000/month
Role Overview
As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact.
Key Responsibilities
Data Science & Machine Learning
- Analyze structured and unstructured data to identify patterns, trends, and business opportunities.
- Perform exploratory data analysis (EDA), feature engineering, and data preparation.
- Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.
- Apply statistical techniques to solve business problems and validate model performance.
- Design and execute experiments to improve model accuracy and business outcomes.
AI Solution Development
- Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.
- Translate business requirements into scalable data science approaches.
- Contribute to Generative AI and advanced analytics initiatives where applicable.
- Document methodologies, model performance, and key findings.
Required Technical Skills
- Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.
- Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.
- Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.
- Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.
- Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.
- Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.
- Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.
- Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.
- Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.
- 2–4 years of experience developing machine learning or data science solutions.
- Experience working on end-to-end data science projects in a business environment.
Nice to Have
- Exposure to Generative AI, LLMs, RAG, or Agentic AI.
- Experience with Computer Vision or Natural Language Processing (NLP).
- Familiarity with cloud-based AI platforms.
- Knowledge of construction, engineering, manufacturing, or industrial domains.
- Participation in hackathons, research, Kaggle competitions, or open-source projects.
Soft Skills
Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.
Job Description – Data Engineer
Role: Data Engineer
Experience: 9+ Years
Location: Bangalore / Hyderabad
Notice Period: Immediate to 15 Days
Interview Process: 1st Round – Virtual | 2nd Round – F2F
Mandatory Skills
- Python
- PySpark
- SQL
- Azure Data Engineering
Job Description
We are looking for an experienced Azure Data Engineer with 9+ years of experience and strong hands-on expertise in Python, PySpark, SQL, and Azure Data Engineering.
Key Responsibilities
- Develop and maintain scalable data engineering solutions using Azure.
- Build and optimize data processing pipelines using PySpark and Python.
- Write complex SQL queries for data extraction and transformation.
- Work with Azure data services and cloud-based data platforms.
- Perform data processing, transformation, and integration.
- Troubleshoot data pipeline and production issues.
- Collaborate with technical and business teams to deliver data solutions.
Preferred: Immediate to 15 Days joiners.
Data Engineer Hiring Post
🚨 Hiring: Data Engineer | PySpark + Python + SQL
We are looking for experienced Data Engineers to join our team!
🔹 Experience: 5 to 9 Years
🔹 Locations: Bangalore / Hyderabad
🔹 Interview Process:
• 1st Round – Virtual
• 2nd Round – Face-to-Face (Karat Test)
🔑 Key Skills:
✅ PySpark
✅ SQL
✅ Python
✅ ETL
📩 Interested candidates can share their updated resume.
#Hiring #DataEngineer #PySpark #Python #SQL #ETL #BangaloreJobs #HyderabadJobs #TechHiring #ImmediateHiring
Hiring for Data Scientist / Senior Data Scientist
Exp : 4 - 12 yrs
Edu : BE/B.tech/MCA
Work Location : Pune
Notice Period : Immediate - 15 days
Skills :
4+ years of experience in data engineering, data science, or related domains.
Hands-on experience with SQL, Python, and distributed data systems.
Knowledge of machine learning techniques and statistical analysis.
Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
Familiarity with DevOps practices and CI/CD for data pipelines.
Platforms & Operations Experience (Preferred)
- Experience working with Azure, AWS, or Google Cloud data tools.
Operational experience with data orchestration tools (Airflow, ADF, Glue).
Understanding of Kubernetes, Docker, or containerized environments.
Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).
Experience in monitoring, logging, and alerting operations for data workflows.
Description
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
- Familiarity with streaming technologies such as Apache Kafka.
- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.
1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Sr.Data Scientist,Python, AI ML
We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.











