27.07.2026 aktualisiert
100 % verfügbar
Senior Data & Analytics Engineer | ETL Pipelines | Cloud Data Platforms | BI Solutions
Berlin, Deutschland
Weltweit
Bachelor of Computer ScienceÜber mich
Senior Data & Analytics Engineer with 5+ years of experience building scalable ETL pipelines, cloud data platforms, and analytics solutions. Skilled in Python, SQL, PySpark, Spark, Airflow, dbt, Kafka, AWS, Azure, GCP, Databricks, and modern data architecture.
Skills
Apache AirflowData ArchitectureDateninfrastrukturData TransformationData Transformation ServicesDaten-VirtualisierungData WarehousingAzure Data LakeAzure Data FactoryLiefer-PipelineApache SparkData LakeApache FlumeAzure Data AnalyticsAzure Synapse Analytics
Data Engineering & ETL Pipelines
Over 5 years of project experience in designing and building scalable ETL/ELT pipelines using Apache Spark, Apache Airflow, and dbt. Expertise in data warehousing, data lakes, delta lake architectures, and data modeling to support large-scale analytics workloads.
Cloud Platforms & Infrastructure
Extensive hands-on experience with AWS, Azure, and Google Cloud Platform (GCP) as well as Databricks. Proficiency in managing Kubernetes-based deployments, CI/CD pipelines, Docker, Terraform, and GitLab CI/CD to ensure reliable and scalable cloud infrastructure.
Programming & Database Technologies
Strong programming skills in Python, SQL, and PySpark. Solid knowledge of databases including MongoDB, Oracle, PostgreSQL, and Snowflake, combined with the ability to optimize SQL queries and ETL workflows for improved processing efficiency.
AI & Machine Learning Integration
Experience in developing LLM-based analytics solutions using OpenAI and LangChain, as well as working with Generative AI, vector databases, prompt engineering, ML pipelines, and feature engineering to support advanced analytics use cases.
Data Quality & Monitoring
Knowledge of pipeline optimization, performance tuning, data validation, and data observability using tools such as Great Expectations to ensure high data quality and reliability across data platforms.
DevOps & Collaboration
Practical experience with DevOps tools including Docker, Kubernetes, CI/CD, Git, and Terraform. Collaboration within Agile/Scrum methodologies using Jira, working effectively with distributed teams to deliver data solutions aligned with business needs.
Big Data Technologies
Proficiency in Apache Spark, Kafka, and Hadoop for processing and managing large-scale data. Experience in building and optimizing big data architectures to handle millions of records for enterprise analytics.
Data Warehousing & Data Lakes
Hands-on experience designing and implementing centralized data lakes and scalable data warehouse architectures, including Snowflake, supporting business growth and handling significant increases in analytical workloads without performance degradation.
Over 5 years of project experience in designing and building scalable ETL/ELT pipelines using Apache Spark, Apache Airflow, and dbt. Expertise in data warehousing, data lakes, delta lake architectures, and data modeling to support large-scale analytics workloads.
Cloud Platforms & Infrastructure
Extensive hands-on experience with AWS, Azure, and Google Cloud Platform (GCP) as well as Databricks. Proficiency in managing Kubernetes-based deployments, CI/CD pipelines, Docker, Terraform, and GitLab CI/CD to ensure reliable and scalable cloud infrastructure.
Programming & Database Technologies
Strong programming skills in Python, SQL, and PySpark. Solid knowledge of databases including MongoDB, Oracle, PostgreSQL, and Snowflake, combined with the ability to optimize SQL queries and ETL workflows for improved processing efficiency.
AI & Machine Learning Integration
Experience in developing LLM-based analytics solutions using OpenAI and LangChain, as well as working with Generative AI, vector databases, prompt engineering, ML pipelines, and feature engineering to support advanced analytics use cases.
Data Quality & Monitoring
Knowledge of pipeline optimization, performance tuning, data validation, and data observability using tools such as Great Expectations to ensure high data quality and reliability across data platforms.
DevOps & Collaboration
Practical experience with DevOps tools including Docker, Kubernetes, CI/CD, Git, and Terraform. Collaboration within Agile/Scrum methodologies using Jira, working effectively with distributed teams to deliver data solutions aligned with business needs.
Big Data Technologies
Proficiency in Apache Spark, Kafka, and Hadoop for processing and managing large-scale data. Experience in building and optimizing big data architectures to handle millions of records for enterprise analytics.
Data Warehousing & Data Lakes
Hands-on experience designing and implementing centralized data lakes and scalable data warehouse architectures, including Snowflake, supporting business growth and handling significant increases in analytical workloads without performance degradation.
Erfahrung
Berufserfahrung5 - 10 Jahre
Freelancer seit2019
Sprachen
DeutschGrundkenntnisseEnglischverhandlungssicher
Projekthistorie
Working remotely from Berlin on two major projects. For Aljasser Holding: designed and built scalable data architecture using Apache Spark and Apache Airflow, reducing end-to-end data processing time from ~4 hours to under 2.5 hours; managed Kubernetes-based deployments and CI/CD pipelines; optimised SQL queries and ETL workflows. For Saudi Paper Group: owned end-to-end data pipeline delivery and orchestration ensuring 99.9% production availability; optimised pipelines reducing average execution time by ~30%; collaborated with distributed teams to deliver AI-driven data solutions. Technologies: Python, Apache Spark, Apache Airflow, SQL, PostgreSQL, dbt, Kubernetes, Docker, GitLab CI/CD, AWS, Azure, Spark, Airflow, AI Solutions, CI/CD.
Based in Karachi, Pakistan. Project EK Retail: developed LLM-based analytics solutions using OpenAI and LangChain, reducing manual insight generation effort by ~40%; designed data pipelines with automated validation improving data quality; built scalable Snowflake data warehouse architecture supporting a 3x increase in analytical workloads. Technologies: Python, SQL, OpenAI, LangChain, Apache Airflow, Snowflake, Data Warehousing, ETL Pipelines, AWS.
Based in Karachi, Pakistan. Project Centralised Data Lake: automated data workflows using Airflow, reducing manual effort by 20%; designed and implemented a centralized data lake improving data accessibility; ensured data consistency through structured database updates and governance processes. Technologies: Python, Airflow, MongoDB, Data Lake, ETL Pipelines, SQL.