Fabric & Alteryx Developer at Ampera Technologies · Remote only · 4 - 8 years · Profitable · Remote only · Posted 11 Nov 2026

Fabric & Alteryx Developer
Experience: 3–6 Years
Location: Remote
Employment Type: Full-Time
Role Overview
We are looking for a skilled professional with experience in Microsoft Fabric, Alteryx, and Python to support data analytics, data engineering, and automation initiatives.
Key Responsibilities
- Work with Microsoft Fabric for data integration, transformation, and analytics.
- Develop and maintain workflows using Alteryx.
- Use Python for data processing, automation, and scripting.
- Build and optimize ETL/ELT pipelines.
- Work with structured and unstructured datasets.
- Perform data validation, troubleshooting, and performance optimization.
- Collaborate with business and technical teams to deliver data-driven solutions.
Required Skills
- Hands-on experience with Microsoft Fabric.
- Strong knowledge of Alteryx workflows.
- Good programming skills in Python.
- Understanding of SQL and database concepts.
- Knowledge of data pipelines, ETL processes, and data transformation.
- Strong analytical and problem-solving skills.

About Ampera Technologies
About
At Ampera Technologies, we empower businesses with cutting-edge data analytics, quality assurance, and data engineering solutions
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Key Skills
Advanced hands-on experience in Alteryx Designer.
Strong knowledge of Alteryx workflows, Macros (Standard, Batch & Iterative).
Excellent SQL skills, including complex queries, joins, CTEs and aggregations.
Strong experience in ETL/ELT, data transformation and integration.
Alteryx workflow performance optimization and troubleshooting.
Experience with Alteryx Server / Alteryx One administration.
Production support, workflow scheduling and deployment.
Knowledge of Snowflake, SQL Server and PostgreSQL.
Microsoft Entra ID and SCIM provisioning knowledge is preferred.
Excellent communication and stakeholder management skills.
Mandatory Requirements
Valid Alteryx Designer Core Certification or higher is mandatory.
Strong hands-on experience in Alteryx workflow development.
Practical experience with Alteryx Macros.
Strong SQL and ETL/ELT expertise.
Experience in production support and performance optimization.
Excellent communication skills.
Good-to-Have Skills
Private Equity / Investment Management domain experience.
Alteryx Designer Advanced or Expert Certification.
Python (Pandas), Snowflake and REST APIs.
Microsoft Entra ID and SCIM 2.0.
Git, CI/CD and workflow automation.
Key Responsibilities
Design, develop and maintain enterprise-grade Alteryx workflows.
Build reusable macros and optimize complex ETL/ELT processes.
Manage workflow deployment, scheduling and monitoring.
Perform performance tuning and troubleshoot production issues.
Integrate multiple databases, APIs and enterprise data sources.
Ensure data accuracy, reconciliation and operational reliability.
Coordinate with business and technical stakeholders.
Immediate Joining
We are looking for a Dedicated Resource on Contract for –
Role: Data Engineer
Experience: 5+ Years
Location: Remote
Duration: 3+ Months
Strong hands-on experience with Snowflake, including writing SQL queries, creating views, stored procedures, and functions.
Good knowledge of AI tools such as Claude.
Experience with ETL tools like Alteryx is good to have.
Power BI experience is good to have.
Strong communication skills.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Sr. Data Engineer
Location: Pune
Responsibilities
· Lead the end-to-end design and development of scalable, high-performance data pipelines and ETL/ELT frameworks aligned with modern data engineering best practices.
· Architect complex data integration workflows that bring together structured, semi-structured, and unstructured data from both cloud and on-premise sources.
· Build robust real-time, batch, and on-demand pipelines with built-in observability—monitoring, alerting, and automated error handling.
· Partner with analysts, data scientists, and business leaders to define and deliver reliable data models, quality frameworks, and SLAs that power key business insights.
· Ensure optimal pipeline performance and throughput, with clearly defined SLAs and proactive alerting for data delivery or quality issues.
· Collaborate with platform, DevOps, and architecture teams to build secure, reusable, and CI/CD-enabled data workflows that align with enterprise architecture standards.
· Establish and enforce the best practices in source control, code reviews, testing automation, and continuous delivery for all data engineering components.
· Lead root cause analysis (RCA) and preventive maintenance for critical data failures, ensuring minimal business impact and continuous service improvement.
· Guide the team in establishing standards for data modeling, transformation logic, and governance, ensuring long-term maintainability and scalability.
· Design and execute comprehensive testing strategies—unit, integration, and system testing—ensuring high data reliability and pipeline resilience.
· Monitor and fine-tune data pipeline and query performance, optimizing for reliability, scalability, and cost-efficiency.
· Create and maintain detailed technical documentation, including data architecture diagrams, process flows, and integration specifications for internal and external stakeholders.
· Facilitate and lead discussions with business and operational teams to understand data requirements, prioritize initiatives, and drive data strategy forward.
Qualifications
· 7 to 10 years of hands-on experience in data engineering roles with a proven record of building scalable and secure data platforms.
· Over 5 years of experience in scripting languages such as Python for data processing, automation, and ETL development.
· 4+ years of experience with Snowflake, including performance tuning, security model design, and advanced SQL development.
· 5+ years of experience with data integration tools such as Azure Data Factory, Fivetran, or Matillion.
· 5+ years of experience in writing complex, highly optimized SQL queries on large datasets.
· Proven experience integrating and managing APIs, JSON, XML, and webhooks for data acquisition.
· Hands-on experience with cloud platforms (Azure/AWS) and orchestration tools like Apache Airflow or equivalent.
· Experience with CI/CD pipelines, automated testing, and code versioning tools (e.g., Git).
· Familiarity with dbt or similar transformation tools and best practices for modular transformation development.
· Exposure to data visualization tools like Power BI for supporting downstream analytics is a plus.
· Strong interpersonal and communication skills with the ability to lead discussions with technical and business stakeholders.
Education
Bachelor’s or Master’s degree in Computer Science/Information technology or related field.
Equivalent academic and work experience can be considered.
1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration
Location – Hyderabad (Hybrid)
Work Experience – 5 to 7 years
CTC – upto 20 LPA
Roles & Responsibilities:
· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.
· Integration of data from multiple sources or vendors to provide the holistic insights from data.
· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.
· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.
· Should have experience in client interaction.
· Experience in mentoring juniors and providing required guidance.
Required Technical Skills
· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.
· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.
· Working knowledge in Databricks, Redshift, ADF etc.
· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.
· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.
· Familiar with SFDC, Waterfall/ Agile methodology.
· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.
Qualifications
· Bachelor’s or master’s Engineering/ MCA or equivalent degree.
· 5-7 years of relevant industry experience as Data Engineer.
· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.
· High motivation, good work ethic, maturity, self-organized and personal initiative.
· Ability to work collaboratively and providing the support to the team.
· Excellent written and verbal communication skills.
· Strong analytical and problem-solving skills.
About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.
As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.
Key Responsibilities:
- Design, develop, test, and maintain optimal data pipeline and ETL architectures.
- Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
- Prepare and optimize data for predictive and prescriptive modeling.
- Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
- Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
- Utilize big data tools and frameworks to optimize data acquisition and preparation.
- Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
- Develop and curate data models for analytics, dashboards, and reports.
- Conduct code reviews, maintain production-level code, and implement testing approaches.
- Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
- Drive innovation and implement efficient new approaches to data engineering tasks.
Must-Have Skills:
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
- 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
- 3–5 years of experience designing and implementing data warehouse solutions.
- Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
- Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
- Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
- Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
- Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
- Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
- Strong problem-solving, communication, and collaboration skills.
Good-to-Have Skills:
- Experience in integrating ERP data into data lakes.
- Experience with traditional ETL tools (e.g., Talend, Pentaho).
Competencies:
- Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
- Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
- Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
- Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python, Hadoop, and Apache Spark.
- Develop efficient data processing and transformation workflows for large datasets.
- Write, optimize, and maintain complex SQL queries and PL/SQL procedures.
- Perform data extraction, transformation, and loading (ETL) from multiple data sources.
- Work with structured and unstructured data to support analytics and reporting requirements.
- Optimize data pipelines and queries for performance, scalability, and reliability.
- Ensure data quality, consistency, security, and integrity across data platforms.
- Collaborate with cross-functional teams to understand business requirements and deliver data engineering solutions.
- Use Git, automation, and CI/CD practices to support development and deployment.
Required Skills
- 4.5–10 years of experience in software development or data engineering.
- Strong proficiency in AWS
- Hands-on experience with Hadoop and Apache Spark.
- Good knowledge of SQL and PL/SQL, including query optimization and stored procedures.
- Experience in ETL development, data processing, and data pipeline design.
- Understanding of data warehousing concepts and distributed computing.
- Strong problem-solving, debugging, and performance-tuning skills.
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Job Description
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Develop data processing solutions using Python.
- Write complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain data ingestion and integration workflows.
- Implement data quality, validation, monitoring, and error-handling processes.
- Develop and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
- Collaborate with data analysts, data scientists, software engineers, and business teams.
- Optimize data pipelines for performance, reliability, and scalability.
- Troubleshoot production data issues and ensure timely resolution.
- Follow best practices for version control, code quality, testing, and deployment.
Mandatory Skills
- Python
- ETL
- SQL
- CI/CD
- DevOps
- Git / Version Control
- Strong problem-solving and debugging skills













