Senior Data Engineer| 7 years of experience | Azure| AWS| Databricks| Snowflake| SQL| Pyspark| Spark| DBT| Airflow| Treasure Data| Kafka
Aktualisiert am 11.08.2026
Profil
Freiberufler / Selbstständiger
Remote-Arbeit
Verfügbar ab: 11.08.2026
Verfügbar zu: 100%
davon vor Ort: 100%
Data Engineer
Datenarchitektur
AWS
Azure
Snowflake
Databricks
Datawarehouse
Azure Devops
Treasure Data
DBT
Airflow
SQL
Apache Spark
Hive
Kafka
Data Analyst
MS Power BI
Tableau
English
Professional Proficiency
German
A2 (actively progressing toward B1)

Einsatzorte

Einsatzorte

Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

6 Monate
2025-11 - 2026-04

Built scalable ETL/ELT pipelines

Data Engineer
Data Engineer
  • Built scalable ETL/ELT pipelines using Azure Databricks, PySpark, and Azure Data Factory for enterprise analytics while participating in Databricks company-wide certification training.
  • Built dbt transformation models on Snowflake to deliver analytics-ready datasets and improve query performance. 
  • Developed Streamlit apps and analytics tools for stakeholders to explore and visualize datasets independently. 
  • Developed AWS Glue and Lambda pipelines, reducing manual data ingestion effort by 40%.
  • Optimized Databricks compute costs by 20% using dbt incremental models and multi-layered ELT workflows.
Databricks
1 Jahr
2024-10 - 2025-09

Built scalable Metadata driven ETL pipelines

Data Engineer
Data Engineer
  • Built scalable Metadata driven ETL pipelines using Azure Databricks, Azure Data Factory, and PySpark for enterprise analytics across UK, France, and Germany applying Microsoft Azure certification best practices.
  • Developed dbt transformation models on Snowflake, improving analytics performance and supporting scalable reporting.
  • Orchestrated cross-cloud data pipelines across AWS using Apache Airflow, accelerating migration delivery by 20%.
  • Built reusable data validation frameworks using PySpark, reducing migration errors by 25%.
  • Improved post-migration support by 40% through comprehensive data lineage documentation and SLA-driven operational processes.
Reckitt
1 Jahr 7 Monate
2023-03 - 2024-09

Built ETL pipelines

Data Engineer
Data Engineer
  • Built ETL pipelines using Azure Data Factory, Azure Databricks, and PySpark for enterprise data processing.
  • Orchestrated Azure and AWS data pipelines using Apache Airflow, improving workflow reliability and automation acquired through company-sponsored certification programs to AWS cloud data engineering projects.
  • Implemented automated monitoring and alerting in Azure Data Factory, reducing data pipeline failures by 10%.
  • Developed Python automation scripts and backend APIs using AWS Lambda to streamline data ingestion.
AGL Hakuhodo
1 Jahr 1 Monat
2021-11 - 2022-11

Designed and implemented ETL pipelines

Data Engineer (Team Lead)
Data Engineer (Team Lead)
  • Designed and implemented ETL pipelines using Azure Databricks, Azure Data Factory, and PySpark to process large-scale sensitive PII datasets.
  • Optimized ETL pipeline performance through parallel processing techniques, reducing data processing time by 9%.
  • Orchestrated Azure and AWS data pipelines using Apache Airflow and Terraform, automating cloud infrastructure provisioning and workflow management.
  • Implemented automated monitoring using AWS CloudWatch, reducing ETL pipeline downtime by 50% through proactive alerting.
  • Optimized AWS Redshift storage using data compression techniques, reducing storage costs by 10% while maintaining query performance.
Paytm
2 Jahre 7 Monate
2019-04 - 2021-10

Developed custom data processing scripts and jobs

Data Engineer
Data Engineer
  • Developed custom data processing scripts and jobs using PySpark to perform complex transformations on the data in Azure Data Factory This included implementing parallelized processing and leveraging Spark's in-memory computing capabilities to enhance performance
  • Developed and optimized data ingestion pipelines in AWS Glue, AWS Redshift, Python, and SQL to ensure smooth and scalable data workflows
Suvidha S. Services
2 Jahre 3 Monate
2017-01 - 2019-03

Freelancing

Consultant
Consultant

Aus- und Weiterbildung

Aus- und Weiterbildung

2012 - 2016

Bachelor of Technology in Electronics and Communication (Major)

Maharishi Dayanand University


2012

K.V (JNU) - High School

Centeral Board Of Secondary Education(CBSE)

Kompetenzen

Kompetenzen

Top-Skills

Data Engineer Datenarchitektur AWS Azure Snowflake Databricks Datawarehouse Azure Devops Treasure Data DBT Airflow SQL Apache Spark Hive Kafka Data Analyst MS Power BI Tableau

Produkte / Standards / Erfahrungen / Methoden

SUMMARY

Senior Data Engineer with 7 years of experience designing and delivering scalable cloud-native data platforms across Azure, AWS, Databricks, and Snowflake. Proven expertise in building robust ETL/ELT pipelines, modern Lakehouse architectures, and analytics-ready datasets using Python, SQL, PySpark, and dbt. Successfully led enterprise cloud migration initiatives, improved data quality through reusable validation frameworks, and optimized large-scale data processing for business-critical analytics. Passionate about building reliable, maintainable, and high-performance data solutions that enable data-driven decision-making.


CAREER HIGHLIGHTS

  • 7 Years of Data Engineering Experience building scalable ETL/ELT solutions across Azure, AWS, Snowflake, Databricks, and PySpark.
  • Multi-Cloud Expertise delivering enterprise data platforms using Azure, AWS, Apache Airflow, Terraform, dbt, and Snowflake.
  • International Delivery Experience supporting enterprise clients across Germany, France, and the UK.
  • Cloud Upskilling completed company-sponsored certification programs in Databricks, Microsoft Azure, AWS, and Snowflake.


RELEVANT SKILLS

  • Cloud Platforms: Microsoft Azure, Amazon Web Services (AWS), Snowflake.
  • Data Engineering: ETL / ELT Pipelines, Azure Databricks, Azure Data Factory, Apache Spark, Airflow, Delta Lake, dbt, Lakehouse Architecture, Data Modeling, Data Quality, Data Validation, Data Governance.
  • Data Warehousing & Databases: Azure Synapse Analytics, Azure Data Lake Storage (ADLS), Amazon Redshift, Amazon S3, Presto, Hive, PostgreSQL, SSMS.
  • DevOps & Engineering Practices: Git, Azure DevOps, CI/CD, Agile/Scrum, Docker, Terraform.
  • Analytics & Visualization: Power BI, Tableau, Streamlit.

Programmiersprachen

Python
SQL
PySpark

Einsatzorte

Einsatzorte

Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

6 Monate
2025-11 - 2026-04

Built scalable ETL/ELT pipelines

Data Engineer
Data Engineer
  • Built scalable ETL/ELT pipelines using Azure Databricks, PySpark, and Azure Data Factory for enterprise analytics while participating in Databricks company-wide certification training.
  • Built dbt transformation models on Snowflake to deliver analytics-ready datasets and improve query performance. 
  • Developed Streamlit apps and analytics tools for stakeholders to explore and visualize datasets independently. 
  • Developed AWS Glue and Lambda pipelines, reducing manual data ingestion effort by 40%.
  • Optimized Databricks compute costs by 20% using dbt incremental models and multi-layered ELT workflows.
Databricks
1 Jahr
2024-10 - 2025-09

Built scalable Metadata driven ETL pipelines

Data Engineer
Data Engineer
  • Built scalable Metadata driven ETL pipelines using Azure Databricks, Azure Data Factory, and PySpark for enterprise analytics across UK, France, and Germany applying Microsoft Azure certification best practices.
  • Developed dbt transformation models on Snowflake, improving analytics performance and supporting scalable reporting.
  • Orchestrated cross-cloud data pipelines across AWS using Apache Airflow, accelerating migration delivery by 20%.
  • Built reusable data validation frameworks using PySpark, reducing migration errors by 25%.
  • Improved post-migration support by 40% through comprehensive data lineage documentation and SLA-driven operational processes.
Reckitt
1 Jahr 7 Monate
2023-03 - 2024-09

Built ETL pipelines

Data Engineer
Data Engineer
  • Built ETL pipelines using Azure Data Factory, Azure Databricks, and PySpark for enterprise data processing.
  • Orchestrated Azure and AWS data pipelines using Apache Airflow, improving workflow reliability and automation acquired through company-sponsored certification programs to AWS cloud data engineering projects.
  • Implemented automated monitoring and alerting in Azure Data Factory, reducing data pipeline failures by 10%.
  • Developed Python automation scripts and backend APIs using AWS Lambda to streamline data ingestion.
AGL Hakuhodo
1 Jahr 1 Monat
2021-11 - 2022-11

Designed and implemented ETL pipelines

Data Engineer (Team Lead)
Data Engineer (Team Lead)
  • Designed and implemented ETL pipelines using Azure Databricks, Azure Data Factory, and PySpark to process large-scale sensitive PII datasets.
  • Optimized ETL pipeline performance through parallel processing techniques, reducing data processing time by 9%.
  • Orchestrated Azure and AWS data pipelines using Apache Airflow and Terraform, automating cloud infrastructure provisioning and workflow management.
  • Implemented automated monitoring using AWS CloudWatch, reducing ETL pipeline downtime by 50% through proactive alerting.
  • Optimized AWS Redshift storage using data compression techniques, reducing storage costs by 10% while maintaining query performance.
Paytm
2 Jahre 7 Monate
2019-04 - 2021-10

Developed custom data processing scripts and jobs

Data Engineer
Data Engineer
  • Developed custom data processing scripts and jobs using PySpark to perform complex transformations on the data in Azure Data Factory This included implementing parallelized processing and leveraging Spark's in-memory computing capabilities to enhance performance
  • Developed and optimized data ingestion pipelines in AWS Glue, AWS Redshift, Python, and SQL to ensure smooth and scalable data workflows
Suvidha S. Services
2 Jahre 3 Monate
2017-01 - 2019-03

Freelancing

Consultant
Consultant

Aus- und Weiterbildung

Aus- und Weiterbildung

2012 - 2016

Bachelor of Technology in Electronics and Communication (Major)

Maharishi Dayanand University


2012

K.V (JNU) - High School

Centeral Board Of Secondary Education(CBSE)

Kompetenzen

Kompetenzen

Top-Skills

Data Engineer Datenarchitektur AWS Azure Snowflake Databricks Datawarehouse Azure Devops Treasure Data DBT Airflow SQL Apache Spark Hive Kafka Data Analyst MS Power BI Tableau

Produkte / Standards / Erfahrungen / Methoden

SUMMARY

Senior Data Engineer with 7 years of experience designing and delivering scalable cloud-native data platforms across Azure, AWS, Databricks, and Snowflake. Proven expertise in building robust ETL/ELT pipelines, modern Lakehouse architectures, and analytics-ready datasets using Python, SQL, PySpark, and dbt. Successfully led enterprise cloud migration initiatives, improved data quality through reusable validation frameworks, and optimized large-scale data processing for business-critical analytics. Passionate about building reliable, maintainable, and high-performance data solutions that enable data-driven decision-making.


CAREER HIGHLIGHTS

  • 7 Years of Data Engineering Experience building scalable ETL/ELT solutions across Azure, AWS, Snowflake, Databricks, and PySpark.
  • Multi-Cloud Expertise delivering enterprise data platforms using Azure, AWS, Apache Airflow, Terraform, dbt, and Snowflake.
  • International Delivery Experience supporting enterprise clients across Germany, France, and the UK.
  • Cloud Upskilling completed company-sponsored certification programs in Databricks, Microsoft Azure, AWS, and Snowflake.


RELEVANT SKILLS

  • Cloud Platforms: Microsoft Azure, Amazon Web Services (AWS), Snowflake.
  • Data Engineering: ETL / ELT Pipelines, Azure Databricks, Azure Data Factory, Apache Spark, Airflow, Delta Lake, dbt, Lakehouse Architecture, Data Modeling, Data Quality, Data Validation, Data Governance.
  • Data Warehousing & Databases: Azure Synapse Analytics, Azure Data Lake Storage (ADLS), Amazon Redshift, Amazon S3, Presto, Hive, PostgreSQL, SSMS.
  • DevOps & Engineering Practices: Git, Azure DevOps, CI/CD, Agile/Scrum, Docker, Terraform.
  • Analytics & Visualization: Power BI, Tableau, Streamlit.

Programmiersprachen

Python
SQL
PySpark

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