Data analyst at Sadup Softech · Bengaluru (Bangalore) · 3 - 6 years · ₹12L - ₹15L / yr · Profitable · Posted 24 Dec 2024

Must have skills
3 to 6 years
Data Science
SQL, Excel, Big Query - mandate 3+ years
Python/ML, Hadoop, Spark - 2+ years
Requirements
• 3+ years prior experience as a data analyst
• Detail oriented, structural thinking and analytical mindset.
• Proven analytic skills, including data analysis and data validation.
• Technical writing experience in relevant areas, including queries, reports, and presentations.
• Strong SQL and Excel skills with the ability to learn other analytic tools
• Good communication skills (being precise and clear)
• Good to have prior knowledge of python and ML algorithms

About Sadup Softech
About
Job role : Golang developer
Experience: 2-5yrs
Location : Bangalore (Hybrid)
Job description :
Golang Engineer - Bangalore
Must have skills2 to 3 years Golang Unix / Linux commands Shell Scripting
* Working experience in building massively scalable high-performance services.
* Excellent problem-solving skills.
* 2-3 years of expertise in GO language (mandatory).
* Expertise in shell scripting.
* Strong Linux systems knowledge.
* Strong working knowledge in Kubernetes is a plus.
* Strong understanding of fundamental distributed system principles.
Connect with the team
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Job Description:
As a Data Science Intern, you will collaborate with our data science and analytics teams to work on meaningful projects involving data analysis, predictive modeling, and statistical modeling. You will have the opportunity to apply your academic knowledge in a practical, fast-paced environment, contribute to key data-driven projects, and gain valuable experience with industry-leading tools and technologies.
Responsibilities:
- Assist in collecting, cleaning, and preprocessing data from various sources.
- Perform exploratory data analysis to identify trends, patterns, and anomalies.
- Develop and implement machine learning models and algorithms.
- Create data visualizations and reports to communicate findings to stakeholders.
- Collaborate with team members on data-driven projects and research.
- Participate in meetings and contribute to discussions on project progress and strategy.
- Work with large datasets to clean, preprocess, and analyze data.
- Build and deploy statistical and machine learning models to generate actionable insights.
- Conduct exploratory data analysis (EDA) to uncover trends, patterns, and correlations.
- Assist in the creation of data visualizations and dashboards for reporting insights.
- Support the development and improvement of data pipelines and algorithms.
- Collaborate with cross-functional teams to understand data needs and translate them into actionable analytics solutions.
- Contribute to the documentation and presentation of results, findings, and recommendations.
- Participate in team meetings, brainstorming sessions, and project discussions.
Duration: 03 Months (with the possibility of extending up to 6 months)
MODE: Work From Home (Online)
Requirements:
- Any Graduate / PassOuts / Freasher can apply.
- Currently pursuing a Bachelor's or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
- Proficiency in programming languages such as Python, R, or SQL.
- Strong foundation in statistics, probability, and data analysis techniques.
Benefits
Internship Certificate
Letter of recommendation
Stipend Performance Based
Part time work from home (2-3 Hrs per day)
5 days a week, Fully Flexible Shift
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.
Company: Wissen Technology
Position: Databricks Engineer
Experience: 6-10 Years
Location: Bengaluru/Mumbai
Employment Type: Full-time
About Wissen Technology
Wissen Technology is a global technology services company focused on delivering innovative software engineering, data, and technology solutions to leading enterprises. The company works with clients across industries to build scalable, high-performance technology platforms and solve complex business and technology challenges.
With a strong focus on engineering excellence, innovation, and collaboration, Wissen Technology brings together skilled technology professionals across areas such as software engineering, data engineering, cloud, analytics, and digital transformation.
At Wissen Technology, employees have the opportunity to work on challenging technology projects, collaborate with experienced engineering teams, and contribute to solutions that create measurable business impact.
Key Responsibilities
- Design, develop, and maintain scalable data processing applications using Python, PySpark, and Spark.
- Develop and optimize data pipelines and workflows on Databricks.
- Collaborate with data engineers, data scientists, business stakeholders, and other technical teams to understand requirements and deliver high-quality solutions.
- Ensure data integrity, quality, performance, and reliability across data processing pipelines.
- Write clean, maintainable, scalable, and efficient code following established coding standards and best practices.
- Perform data analysis and implement appropriate data validation and quality checks.
- Monitor, troubleshoot, and optimize performance issues across data workflows and pipelines.
- Work with relational databases and develop efficient SQL queries for data extraction and transformation.
- Participate in code reviews, testing, deployment, and continuous improvement of data engineering solutions.
- Use Git/version control and follow established software development and deployment practices.
Required Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
- Proven experience as a Databricks Developer, Data Engineer, or similar role.
- Strong hands-on expertise in Apache Spark and PySpark.
- Strong programming skills in Python; experience with Scala is an advantage.
- Strong proficiency in SQL and hands-on experience with relational databases.
- Practical experience developing and optimizing data pipelines and data processing applications.
- Familiarity with Git and version control systems.
- Strong understanding of data engineering concepts, data transformation, and data validation.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
9+yrs
Bangalore/Hyderabad
immediate to 15days.
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.
Data Engineer - Remote
Nearshore engineer on a team converting SAS code to Python and SQL on Databricks using generative AI. You will work with the existing accelerators, own deliverables end to end, and communicate directly with client and partner stakeholders.
Required for both:
4+ years of professional data or software engineering experience
Strong Python and SQL
Hands-on Databricks (Unity Catalog, Workflows, Databricks Asset Bundles)
GitLab CI/CD: pipelines, merge request workflows, automated testing
Git branching and code review discipline
Clear written and spoken English with client-facing partners
Demonstrated ownership: scoping, delivering, and flagging risk without prompting
Focus: Pipeline reliability, validation, and delivery of converted code.
Responsibilities:
Build and run the pipelines that process SAS inventories and converted outputs
Validate converted code for parity against SAS outputs (row counts, checksums, schema, data types)
Own deployment through DABs and GitLab CI/CD
Manage Unity Catalog objects, permissions, and environment promotion
Troubleshoot job failures and performance issues
Required:
Spark and Delta Lake performance tuning
Data validation and reconciliation experience
Infrastructure as code or DAB-based deployment experience
Nice to have:
SAS reading ability, healthcare data exposure, Azure.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/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
This role will be permanent with NAM info and deploy to client location Hyderabad & Pune.
Work Mode: WORK FROM OFFICE
Role Descriptions:
- Perform detailed data analysis and support business decision-making
- Gather and document business requirements and translate them into technical specifications
- Work closely with stakeholders to define data needs and reporting requirements
- Create user stories, functional specifications, and support UAT activities
- Ensure alignment between business objectives and data solutions
Required Skills:
- Strong expertise in SQL and data querying
- Proven experience in data analysis, requirement gathering, and stakeholder management
- Ability to translate business requirements into technical solutions and user stories
- Good understanding of data models, reporting, and analytics concepts
Skills: Business Analysis~ORACLE SQL
Locations: ~HYDERABAD~PUNE~
Desire candidate
- Candidate should have valid PF.
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.











