{"id":2141355,"url":"https://alion.io/job/mastek-data-engineerbi-developer-daa","title":"Data Engineer/BI Developer-DA&A","company":{"id":59435,"name":"Mastek","domain":"mastek.com","url":"https://alion.io/company/mastek","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":56},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache NiFi","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Hadoop","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Salesforce Data Cloud","optional":false},{"name":"Spring Boot","optional":false},{"name":"Apex","optional":true}],"status":"live","first_seen_at":"2026-09-29T00:00:00Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-11T18:14:10Z","board_verified":true,"closed_at":null,"days_open":13,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":13},"description":"Job Title\nData Engineer / BI Developer - DA&A\nExpected Work Experience\n5 to 7 Years\nJob Location\nIndia\nJob Summary\nThis role focuses on designing and building scalable, cloud-native data pipelines and services while working closely with the Salesforce platform and engineering teams. The position will support the transition of legacy workflows (e.g., NiFi, Java APIs) to modern architectures leveraging GCP and Salesforce Data Cloud. It requires a strong data engineering foundation combined with working knowledge of Salesforce data models, integrations, and platform capabilities. Candidate must have relevant experience of 5 to 7 Years.\nKey Responsibilities\nBuild and operate data pipelines in cloud environments (GCP preferred) with integration into Salesforce Data Cloud.\nMigrate and modernize legacy workflows to cloud-native solutions (e.g., Dataflow, Pub/Sub).\nDesign and implement distributed data processing systems using technologies such as Spark and the Hadoop ecosystem.\nDevelop and maintain integrations between Salesforce and external systems using APIs and event-driven patterns.\nCollaborate with Salesforce teams on data modeling, ingestion, and synchronization strategies.\nApply working knowledge of Salesforce platform fundamentals (data model, security, APIs) in solution design.\nDevelop backend services using Java and Spring Boot to support data and integration use cases.\nEnsure observability, reliability, and performance tuning of data systems and pipelines.\nUse containerization technologies such as Docker and Kubernetes and CI/CD practices for efficient deployments.\nImplement data engineering best practices to support Data Automation & AI and analytics use cases.\nWork closely with BI and analytics stakeholders to ensure data pipelines and models effectively support reporting and insight generation.\nContribute to the modernization of data workflows to leverage GCP, Salesforce Data Cloud, and DataBricks where applicable.\nMaintain clear documentation for data flows, integrations, and operational procedures to support ongoing maintenance and knowledge sharing.\nOther Capabilities\nAbility to design reliable, scalable data pipelines operating seamlessly across GCP and Salesforce Data Cloud.\nCapability to drive smooth migration of legacy systems with minimal disruption to downstream consumers.\nStrong focus on well-integrated data flows between Salesforce and external systems with clear ownership and observability.\nCommitment to improved operational efficiency through robust design, monitoring, and engineering best practices.\nCollaborative mindset to work effectively with Salesforce, data, and BI teams.\nProblem-solving skills to troubleshoot complex data integration and performance issues in distributed environments.\nQualifications and Skills\nProven experience (5 to 7 years) as a Data Engineer or BI Developer in data analytics and data engineering environments.\nStrong hands-on experience with cloud platforms, preferably GCP, including services such as Dataflow and Pub/Sub.\nExperience designing and implementing distributed data processing systems using Spark and the Hadoop ecosystem.\nWorking knowledge of Salesforce Data Cloud and Salesforce platform fundamentals, including data models, security, and APIs.\nExperience developing backend services using Java and Spring Boot for data and integration use cases.\nProficiency in building and maintaining API-based and event-driven integrations between Salesforce and external systems.\nFamiliarity with containerization and orchestration tools such as Docker and Kubernetes.\nExperience with CI/CD pipelines and modern software engineering practices for data solutions.\nExposure to DataBricks and related data analytics tooling is preferred.\nStrong understanding of data modeling, data ingestion, and synchronization strategies for analytics and BI.\nSolid grasp of observability practices, including logging, monitoring, and alerting for data pipelines and services.\nAbility to write clean, maintainable code and follow best practices in version control and collaborative development.\nGood communication skills and the ability to work in cross-functional teams across data, engineering, and business 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