{"id":2927249,"url":"https://alion.io/job/aays-analytics-principal-data-engineer","title":"Principal Data Engineer","company":{"id":3908009,"name":"Aays Analytics","domain":"aaysanalytics.com","url":"https://alion.io/company/aays-analytics","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":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":31000,"max_usd":67000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":20},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Data Vault","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google GKE","optional":false},{"name":"IAM","optional":false},{"name":"Looker","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Time Series","optional":false},{"name":"Vertex AI","optional":false},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-20T13:35:43Z","employer_posted_date":null,"last_verified_at":"2026-10-20T13:35:43Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"You will act as a key member of the consulting team, helping clients to reinvent their corporate finance function by leveraging advanced analytics. You will be working closely and directly with senior stakeholders of the clients, designing and implementing data strategy in the finance space, which includes multiple use cases, viz., controllership, FP& A, and GPO. You will be responsible for developing technical solutions to deliver scalable analytical solutions leveraging cloud and big data technologies. You will also collaborate with business consultants and product owners to design and implement technical solutions. Communication and organizational skills are key for this position.\n\nResponsibilities: \nDesign and drive end-to-end data and analytics solution architecture from concept to delivery on Google Cloud Platform and Azure.\nDesign, develop, and support conceptual, logical, and physical data models for advanced analytics and ML-driven solutions.\nEnsure integration of industry-accepted data architecture principles, standards, guidelines, and concepts with other domains, along with coordinated roll-out and adoption strategies.\nDrive the design, sizing, provisioning, and setup of GCP and Azure environments and related services such as BigQuery, Dataflow, and Cloud Storage.\nProvide mentoring and guidance on GCP and Azure-based data architecture to engineering, analytics, and business teams.\nReview solution requirements and architecture for appropriate technology selection, efficient resource utilization, and effective integration across systems and technologies.\nAdvise on emerging GCP and Azure trends and services, and recommend adoption strategies to maintain a competitive edge.\nActively participate in pre-sales engagements and PoCs and contribute to publishing thought leadership content.\nCollaborate closely with the founders and leadership team to shape and drive the organization's cloud and data strategy.\n\nRequirements: \nDemonstrated experience in delivering multiple data and analytics solutions on GCP and Azure.\nHands-on experience with data ingestion, processing, and orchestration tools such as Dataflow, Pub/Sub, Dataproc, Cloud Composer, and Data Fusion.\nDeep expertise with GCP and Azure data warehousing and analytics services, including BigQuery, Cloud Storage, and Looker.\nFamiliar with Data Mesh, Data Fabric, and Data Products, Data Contracts, and experience in Data Mesh implementation.\nStrong understanding and practical experience with different data modeling techniques (relational, star, snowflake, Data Vault, etc. ) and working with transactional, time-series, and unstructured datasets.\nExperience with enterprise data management, i. e., data quality, metadata management, data governance, and data observability using GCP and Azure-native or third-party tools.\nExperience in the design and implementation of event-driven architecture and tools like Google Pub/Sub or Kafka will be an added advantage.\nFamiliar with AI, GenAI concepts, and Vertex AI.\nSolid grasp of operational dependencies and integration across applications, networks, security, and infrastructure in the cloud, including IAM, VPCs, VPNs, firewall rules, GKE, and service accounts.\nStrong foundation in computer science or software engineering, with expertise in software development methodologies and Dev/Data Ops and CI/CD.\nPractical experience using tools such as Terraform, Cloud Build, GitHub Actions, and scripting via Python, Bash, etc.\nFamiliar with the software development lifecycle and cloud-native application development.\nRemains hands-on with technology and stays current with industry trends and GCP and Azure service evolution.\nDemonstrated hands-on experience coding in Python, SQL, and Spark, with the flexibility to pick up new languages or technologies quickly.\nGCP and Azure professional data engineer certifications will be an added advantage.\nSkills\nAzure, BigQuery, CI/CD, Data Mesh, Dataflow, GCP, Google Cloud Platform, Kafka, Pub/Sub, Python, Spark, Terraform, data modeling","description_format":"text","description_chars":4030,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Analytics & BI Consulting"],"lifecycle":[{"event":"open","at":"2026-10-20T13:35:43Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":27,"reasons":["seen:3","velocity","win:early"],"computed_at":"2026-10-24T06:02:35Z"},"pay":null,"html_url":"https://alion.io/job/aays-analytics-principal-data-engineer","json_url":"https://alion.io/job/aays-analytics-principal-data-engineer.json","meta":{"generated_at":"2026-10-24T08:02:02Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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