{"id":2803468,"url":"https://alion.io/job/pravi-hr-advisory-data-engineer-etldata-pipeline","title":"Data Engineer - ETL/Data Pipeline","company":{"id":3800706,"name":"Pravi HR Advisory","domain":"pravihr.com","url":"https://alion.io/company/pravi-hr-advisory","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Azure","optional":true},{"name":"dbt","optional":true},{"name":"MQTT","optional":true}],"status":"closed","first_seen_at":"2026-07-22T08:14:04Z","employer_posted_date":null,"last_verified_at":"2026-10-20T08:14:37Z","board_verified":false,"closed_at":"2026-10-20T08:14:37Z","days_open":90,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":90},"description":"Position: Data Engineer Data & AI\n\nThe successful candidate will develop, integrate, and maintain data solutions for digital products, data platforms, and AI applications across the company and within the R&D environment.\n\nThey will ensure that process, equipment, product, and business data can be used in a structured, quality-assured, and production-ready manner. In doing so, they will make a significant contribution to building a scalable Data & AI foundation and delivering data-driven R&D products and internal AI applications.\n\nTechnical and Project Responsibilities:\n\n- Independently develop and maintain data pipelines, data models, and interfaces for digital products and AI use cases\n\n- Integrate data from internal and external sources, particularly process, equipment, automation, laboratory, and business systems\n\n- Prepare and transform data for analytics, machine learning, reporting, and AI applications\n\n- Contribute to the development of standardized data products, data architectures, and reusable Data & AI patterns\n\n- Ensure the traceability, documentation, and technical maintainability of the data solutions within your area of responsibility\n\n- Support the evaluation of new AI and data use cases from a software engineering and technical feasibility perspective\n\n- Collaborate with software development, cloud and platform engineering, data science, process engineering, domain experts, and IT teams\n\nTechnical Requirements:\n\n- Strong knowledge of building data pipelines, data models, and ETL/ELT processes\n\n- Strong proficiency in SQL, PySpark/Spark, and Python, as well as experience with MLflow and data-driven analytics and development tools\n\n- Experience with databases, APIs, interfaces, data formats, and data integration\n\n- Basic understanding of modern cloud, container, and Kubernetes-based platforms\n\n- Knowledge of data quality, data validation, technical documentation, and monitoring\n\n- Ability to translate business and technical requirements into structured, scalable, and maintainable data solutions\n\n- Desirable: Experience with Azure, Stackable, data lake or lakehouse architectures, Kafka, MQTT, Airflow, dbt, or comparable technologies\n\nPersonal and Interpersonal Skills:\n\n- Willingness and ability to learn and become proficient in new technologies\n\n- Analytical and structured approach to work\n\n- Initiative and a strong sense of responsibility\n\n- Ability to identify opportunities for innovation and optimization\n\n- Strong teamwork and collaboration skills in interdisciplinary and international environments\n\n- Excellent written and spoken English, with the ability to communicate effectively with colleagues and stakeholders in Germany\n\n- German language skills are an advantage but not required\n\n- Clear communication tailored to different audiences\n\n- Reliability, pragmatism, and a strong commitment to quality\n\nEducation & Experience Requirements:\n\n- Bachelors degree in computer, Information Systems or related specialization in IT\n\n- 5 to 8 years of relevant experience.\nSkills\nSQL, Python, Spark, ETL, Data Modeling, Data Pipeline, Data Engineering, Apache Spark, Data Integration, 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