{"id":2811956,"url":"https://alion.io/job/hcltech-solution-architect-21","title":"Solution Architect","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":92000,"max_usd":162000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":47},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache 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ETL/ELT pipelines for structured and unstructured data.\nBuild batch and real-time processing solutions using BigQuery, Dataflow, Cloud Storage, Pub/Sub, and related GCP services.\nDevelop data-processing components and integrations using Java or Python, SQL, REST APIs, Kafka, and containerized services on GKE.\nImplement reusable ingestion and transformation frameworks supporting full, incremental, and event-driven loads.\nDesign data models and optimize BigQuery tables through partitioning, clustering, efficient SQL, and cost-aware processing patterns.\nProduce high-level and low-level technical designs, document assumptions, and contribute to architecture reviews.\nImplement data-quality checks, schema validation, reconciliation, audit logging, lineage, monitoring, alerting, and error-handling mechanisms.\nTroubleshoot complex production issues, perform root-cause analysis, and deliver sustainable corrective actions.\nApply security, privacy, access-control, reliability, and operational-support standards across data solutions.\nUse source control, automated testing, CI/CD, and infrastructure-as-code practices to promote repeatable deployments.\nParticipate in code reviews, improve engineering standards, and mentor less-experienced engineers.\nCollaborate with architects, analysts, application teams, platform teams, and business stakeholders to deliver reliable data products.\nRequired Technical Skills\nStrong hands-on experience with GCP data services, particularly BigQuery, Dataflow, Cloud Storage, and Pub/Sub.\nProficiency in SQL, including complex transformations, query tuning, data validation, and analytical processing.\nProficiency in Java or Python for data pipelines, automation, API integration, and production support.\nGood understanding of ETL/ELT, data warehousing, data lakes, dimensional modelling, batch processing, and stream processing.\nExperience with Apache Beam, Kafka, REST APIs, Docker, Kubernetes, or GKE.\nExperience with data formats such as JSON, CSV, Avro, and Parquet.\nWorking knowledge of Git, automated testing, CI/CD pipelines, observability, and release management.\nAbility to design solutions for scalability, resilience, security, performance, operability, and cost efficiency.\nPreferred Skills\nExperience with Cloud Composer or Apache Airflow, Dataproc or Spark, Dataform or dbt, and metadata-driven pipeline frameworks.\nExposure to Terraform or another infrastructure-as-code tool.\nKnowledge of Dataplex, data governance, metadata management, lineage, and access-control practices.\nExperience modernizing legacy or on-premises data workloads to GCP.\nGoogle Cloud Professional Data Engineer certification or an equivalent cloud data certification.\nTypical Qualifications\nDegree in Computer Science, Software Engineering or a related discipline, or equivalent practical experience.\nExperience delivering software solutions in agile teams.\nKnowledge of modern development frameworks, tools and engineering practices.\nKey Responsibilities\nKey Responsibilities\nDesign, develop, test, deploy, and maintain scalable ETL/ELT pipelines for structured and unstructured data.\nBuild batch and real-time processing solutions using BigQuery, Dataflow, Cloud Storage, Pub/Sub, and related GCP services.\nDevelop data-processing components and integrations using Java or Python, SQL, REST APIs, Kafka, and containerized services on GKE.\nImplement reusable ingestion and transformation frameworks supporting full, incremental, and event-driven loads.\nDesign data models and optimize BigQuery tables through partitioning, clustering, efficient SQL, and cost-aware processing patterns.\nProduce high-level and low-level technical designs, document assumptions, and contribute to architecture reviews.\nImplement data-quality checks, schema validation, reconciliation, audit logging, lineage, monitoring, alerting, and error-handling mechanisms.\nTroubleshoot complex production issues, perform root-cause analysis, and deliver sustainable corrective actions.\nApply security, privacy, access-control, reliability, and operational-support standards across data solutions.\nUse source control, automated testing, CI/CD, and infrastructure-as-code practices to promote repeatable deployments.\nParticipate in code reviews, improve engineering standards, and mentor less-experienced engineers.\nCollaborate with architects, analysts, application teams, platform teams, and business stakeholders to deliver reliable data products.\nRequired Technical Skills\nStrong hands-on experience with GCP data services, particularly BigQuery, Dataflow, Cloud Storage, and Pub/Sub.\nProficiency in SQL, including complex transformations, query tuning, data validation, and analytical processing.\nProficiency in Java or Python for data pipelines, automation, API integration, and production support.\nGood understanding of ETL/ELT, data warehousing, data lakes, dimensional modelling, batch processing, and stream processing.\nExperience with Apache Beam, Kafka, REST APIs, Docker, Kubernetes, or GKE.\nExperience with data formats such as JSON, CSV, Avro, and Parquet.\nWorking knowledge of Git, automated testing, CI/CD pipelines, observability, and release management.\nAbility to design solutions for scalability, resilience, security, performance, operability, and cost efficiency.\nPreferred Skills\nExperience with Cloud Composer or Apache Airflow, Dataproc or Spark, Dataform or dbt, and metadata-driven pipeline frameworks.\nExposure to Terraform or another infrastructure-as-code tool.\nKnowledge of Dataplex, data governance, metadata management, lineage, and access-control practices.\nExperience modernizing legacy or on-premises data workloads to GCP.\nGoogle Cloud Professional Data Engineer certification or an equivalent cloud data certification.\nTypical Qualifications\nDegree in Computer Science, Software Engineering or a related discipline, or equivalent practical experience.\nExperience delivering software solutions in agile teams.\nKnowledge of modern development frameworks, tools and engineering practices.\nSkill Requirements\nOther Requirements","description_format":"text","description_chars":6146,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","Systems Integrators"],"lifecycle":[{"event":"open","at":"2026-10-18T09:46:44Z"}],"visa":[],"liveness":{"score":99,"band":"hot","label":"Hiring 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