{"id":3232999,"url":"https://alion.io/job/accenture-data-engineer-70","title":"Data Engineer","company":{"id":271,"name":"Accenture","domain":"accenture.com","url":"https://alion.io/company/accenture","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":2094,"ghost_share":0.001,"stale_share":0.146,"repost_share":0.006,"time_to_fill_p50_days":5,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":33000,"max_usd":61000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Snowflake","optional":false},{"name":"Amazon S3","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Azure DevOps","optional":true},{"name":"Blue-Green Deployment","optional":true},{"name":"CI/CD","optional":true},{"name":"Data Vault","optional":true},{"name":"dbt","optional":true},{"name":"Fivetran","optional":true},{"name":"GCP","optional":true},{"name":"GDPR","optional":true},{"name":"GitHub Actions","optional":true},{"name":"GitLab","optional":true},{"name":"Jenkins","optional":true},{"name":"Machine Learning","optional":true},{"name":"Python","optional":true},{"name":"SLI/SLO/SLA","optional":true},{"name":"SQL","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-23T00:00:00Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-29T03:56:50Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Project Role : Data EngineerProject Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.\nMust have skills : Data Engineering, Snowflake Data Warehouse\nGood to have skills : Machine Learning (ML)\nMinimum 12 year(s) of experience is required\nEducational Qualification : 15 years full time education\nSummary\nLead the architecture, strategy, and delivery of enterprise-scale data platforms on Snowflake. Own\ntechnical direction for data modeling, ingestion, performance, security, governance, and developer\nexperience. Mentor engineers and collaborate with stakeholders to deliver robust, scalable, and\nsecure data solutions for analytics, AI/ML, and operational use cases.\nRoles and responsibilities:\nArchitecture & Strategy\nDefine target data platform architecture (multi-environment, multi-account, integration\npatterns).\nEstablish technical standards for ELT, dbt/Snowpark, data contracts, and lifecycle\nmanagement.\nLead make/buy/standardize decisions for connectors, CDC/integration tools, orchestration,\ncatalog, and observability.\nDesign and Implement CI/CD pipelines for data engineering workflows\nDesign and Implement Streaming data architectures and Micro-service based architectures\nDesign and implement reliable ingestion and transformation pipelines (batch/streaming) using\nSnowflake features (Snowpipe, Streams & Tasks, external stages) and orchestration tools\n(Airflow/ADF).\nDrive data modeling best practices (dimensional, data vault, wide tables) with versioning,\ntesting, and documentation.\nEnable CI/CD, environment promotion, automated data quality checks (dbt tests, Great\nExpectations), and blue-green deployments.\nPerformance, Reliability & Cost\nLead workload management, query optimization, clustering, and caching strategies.\nImplement resource monitors, autosuspend policies, and cost observability dashboards.\nOwn SLA/SLOs for key data products, incident runbooks, lineage-aware impact analysis, and\npost-incident reviews.\nSecurity, Compliance & Sharing\nDefine and enforce RBAC/ABAC, row/column-level security, masking policies, and secrets\nmanagement.\nPartner with Security/GRC on auditing, data retention, PII/PHI protection, and regulatory\ncompliance (GDPR/CCPA).\nOperationalize secure data sharing and cleanroom patterns for internal/external collaboration.\nLeadership & Influence\nServe as principal technical authority for Snowflake mentor engineers and elevate team\ncapability.\nCollaborate with Product, Analytics, and ML teams to deliver scalable, reusable data products.\nAuthor architecture decision records (ADRs), roadmaps, and executive-level technical\nnarratives.\nTechnical experience & Professional attributes:\n12+ years in data engineering/architecture 6+ years designing and operating Snowflake at scale\n(multi-TB warehouses, 1000s of daily jobs).\nExpert SQL and deep knowledge of Snowflake internals: virtual warehouses, micropartitions,\nclustering, Query Profile, caching, Time Travel, Failsafe.\nHands-on with Snowflake workloads & features: Snowpipe, Streams & Tasks, stages/external\ntables, materialized views, Secure Data Sharing.\nExperience with at least one transformation framework (dbt strongly preferred) and\nprogramming language (Python, Snowpark, UDFs).\nExperience with orchestration (Airflow/ADF/Argo), CI/CD (Jenkins/GitHub Actions/GitLab/Azure\nDevOps), and IaC (Terraform).\nFluency with cloud platforms (AWS/Azure/GCP), object storage (S3/ADLS/GCS), networking\n(VPC/VNet, PrivateLink/Private Endpoints).\nSolid grounding in data governance (catalog/lineage tools), privacy & security controls, and\nobservability (logs/metrics/traces for pipelines).\nExperience in Fivetran and streaming tools Kafka, Pulsar or other equivalent.\nPerformance tuning at scale: warehouse sizing, task concurrency, pruning/clustering, cost\noptimization.\nExcellent communication able to present architecture tradeoffs to engineers and executives.\nPreferred Skills\nSnowPro Advanced: Architect or Advanced: Data Engineer certification.\nData quality frameworks ,data contracts, and contract-testing patterns.\nAdditional Information:\nYou will be working with a Trusted Tax Technology Leader, committed to delivering reliable and innovative solutions\nStrategic Leadership: Ability to influence technology direction and align solutions with business objectives.\nMentorship & Talent Development: Guide and coach engineers foster an inclusive and high-performing team culture.\nExcellent Communication Skills: Strong verbal, written, and presentation skills for technical and non-technical audiences.\nBusiness Acumen: Understand business priorities and translate them into actionable technical strategies.\nChange Management & Stakeholder Engagement: Drive adoption of new processes and manage organizational change effectively.\nDecision-Making & Problem-Solving: Demonstrate sound judgment in complex, ambiguous situations.15 years full time education\nAbout Accenture\nAccenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us atwww.accenture.com\nEqual Employment Opportunity Statement\nWe believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, militaryveteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicablelaw. 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