{"id":1227817,"url":"https://alion.io/job/strategic-hr-solutions-platform-data-engineer","title":"Platform Data Engineer","company":{"id":3800623,"name":"Strategic HR Solutions","domain":"strategichr.org","url":"https://alion.io/company/strategic-hr-solutions","size_band":null,"is_staffing_agency":true,"employer_type":"agency","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":["Pune, India","Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19000,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"Apache NiFi","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Linux","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false},{"name":"Ubuntu","optional":false},{"name":"Ansible","optional":true},{"name":"Chef","optional":true},{"name":"Fluentd","optional":true},{"name":"Kubernetes","optional":true},{"name":"Power BI","optional":true},{"name":"Python","optional":true},{"name":"SIEM","optional":true}],"status":"live","first_seen_at":"2026-09-23T04:30:12Z","employer_posted_date":null,"last_verified_at":"2026-09-23T04:30:12Z","board_verified":false,"closed_at":null,"days_open":40,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":40},"description":"Platform Data Engineer\n\nPrimary Skills :\n\n- Azure Data Factory\n\n- Databricks\n\n- PySpark\n\n- Azure Cloud Services\n\n- Data Engineering, Kafka, Infrastructure Automation\n\nRole Summary :\n\nWe are seeking an experienced Platform Data Engineer to join the Global Cybersecurity Data Acquisition and Engineering team. The role is responsible for designing, developing, and supporting enterprise-scale data ingestion pipelines that onboard security data into a cyber data lake and analytics platform.\n\nThe ideal candidate :\n\nThe ideal candidate will have strong expertise in Azure-based data engineering solutions, Databricks, PySpark, and cloud-native technologies. This role requires hands-on experience building reliable, scalable, and performant data pipelines while collaborating with cybersecurity, infrastructure, and analytics teams to deliver high-quality security data for advanced analytics and threat detection.\n\nKey Responsibilities :\n\n- Design, develop, and maintain scalable data ingestion and integration pipelines using Azure Data Factory, Databricks, and PySpark.\n\n- Develop and support secure, reliable, and high-performance data acquisition patterns for the cyber analytics platform.\n\n- Lead technical enhancements across existing and future analytics technologies including Databricks, Data Factory, Kafka, NiFi, and related platforms.\n\n- Build and optimize automation and orchestration capabilities across the cybersecurity data platform.\n\n- Support the development and deployment of security analytics and detection use cases.\n\n- Collaborate with cybersecurity teams, infrastructure teams, and business stakeholders to implement data-driven security solutions.\n\n- Drive continuous improvement initiatives across platform engineering, data quality, monitoring, and operational processes.\n\n- Provide technical guidance and mentorship to team members and promote engineering best practices.\n\n- Support platform monitoring, troubleshooting, and performance optimization activities.\n\n- Ensure solutions follow security, governance, and operational excellence standards.\n\nPrimary Skills (Must Have) :\n\n1. Data Engineering & Analytics :\n\n- Azure Data Factory (ADF)\n\n- Databricks\n\n- PySpark\n\n- Data Pipeline Development\n\n- Data Ingestion & Transformation\n\n- ETL / ELT Processes\n\n- Data Quality and Data Cleansing\n\n2. Cloud Platform :\n\n- Microsoft Azure\n\n- Azure Storage Services\n\n- Azure Functions\n\n- Azure Compute Services\n\n- Azure Networking\n\n- Azure Identity & Access Management\n\n3. Streaming & Real-Time Processing :\n\n- Apache Kafka\n\n- Azure Event Hubs\n\n- Spark Streaming\n\n- Real-Time Data Processing\n\n4. Infrastructure & Automation :\n\n- Infrastructure as Code (Terraform / ARM)\n\n- Automation Tools\n\n- CI/CD Concepts\n\n- Cloud Infrastructure Management\n\n5. Operating Systems :\n\n- Linux Administration (RHEL / Ubuntu)\n\nSecondary Skills (Nice to Have) :\n\n- Apache NiFi\n\n- Fluentd\n\n- Azure Power BI\n\n- Azure Containers and Kubernetes\n\n- Chef / Ansible\n\n- Cloud-based SIEM Platforms\n\n- SOAR Technologies\n\n- Cybersecurity Analytics Platforms\n\n- Security Data Management\n\nKey Competencies :\n\n- Strong leadership and technical problem-solving abilities.\n\n- Excellent stakeholder management and collaboration skills.\n\n- Experience working in large-scale enterprise environments.\n\n- Ability to design sustainable, scalable, and secure platform solutions.\n\n- Strong troubleshooting and performance optimization expertise.\n\n- Continuous learning mindset and interest in cybersecurity technologies.\n\n- Effective communication and mentoring capabilities.\n\nExperience & Qualifications :\n\n- 5 - 7 years of experience in Data Engineering, Platform Engineering, or Cloud Data Solutions.\n\n- Hands-on experience with Azure Data Factory, Databricks, and PySpark.\n\n- Proven experience building and optimizing cloud-based data pipelines.\n\n- Strong understanding of real-time data processing and streaming technologies.\n\n- Experience with Azure cloud services and infrastructure automation tools.\n\n- Knowledge of cybersecurity data platforms, security analytics, or SIEM ecosystems is preferred.\n\n- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.\n\nWays of Working :\n\n- Work closely with Cybersecurity, Infrastructure, and Analytics teams to deliver strategic data engineering solutions.\n\n- Drive continuous enhancement of the enterprise cyber data lake and analytics ecosystem.\n\n- Participate in platform modernization, automation, and operational excellence initiatives.\n\n- Support end-to-end ownership of data onboarding, engineering, monitoring, and optimization activities.\n\n- Contribute to knowledge sharing, technical mentoring, and engineering best practices across the team.\nSkills\nData Engineering, Azure, Databricks, PySpark, Azure Data Factory, Kafka, Data Pipeline, ETL, Power BI","description_format":"text","description_chars":4828,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Information Security"],"lifecycle":[{"event":"open","at":"2026-09-25T13:06:44Z"}],"visa":[],"liveness":{"score":14,"band":"cold","label":"Long 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