{"id":1569194,"url":"https://alion.io/job/pricewaterhousecoopers-etic-aws-data-engineer-senior-associate","title":"ETIC, AWS Data Engineer, Senior Associate","company":{"id":5739,"name":"PwC","domain":"pwc.com","url":"https://alion.io/company/pwc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":70,"open_postings":2647,"ghost_share":0.507,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":26,"computed_at":"2026-10-23T05:54:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cairo, Egypt"],"countries":["EG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":56000,"max_usd":145000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2491},"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"Databricks","optional":true},{"name":"Hadoop","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2025-10-22T00:00:00Z","employer_posted_date":"2025-10-22","last_verified_at":"2026-10-22T13:02:42Z","board_verified":true,"closed_at":null,"days_open":366,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":366},"description":"Line of Service\nAdvisoryIndustry/Sector\nTechnologySpecialism\nAdvisory - OtherManagement Level\nSenior AssociateJob Description & Summary\nAs a Senior Associate in the Data Engineering team, you will play a key role in designing, building, and optimizing modern data platforms and pipelines on AWS. You will work within cross-functional teams to deliver scalable, secure, and high-performing data solutions that enable advanced analytics, AI, and business insights for enterprise clients.This role requires a strong understanding of cloud data architecture and hands-on experience with AWS data services for batch and real-time data engineering.\nKey Responsibilities\nDesign, develop, and maintain end-to-end data pipelines across structured, semi-structured, and unstructured data sources.\nImplement data ingestion, transformation, and orchestration frameworks leveraging AWS Glue, Amazon Redshift, AWS Step Functions, and Amazon Managed Workflows for Apache Airflow (MWAA).\nDevelop and optimize ETL/ELT processes using PySpark, SQL, and Delta Lake to ensure high performance and scalability.\nImplement and enforce data quality, lineage, and governance practices.\nWork closely with solution architects to design modern data architectures and ensure compliance with security and privacy standards.\nParticipate in client workshops and technical discussions to translate business needs into technical designs.\nRequired Skills & Experience\n3-6 years of experience in data engineering, preferably in a consulting or enterprise environment.\nStrong hands-on experience with: AWS Data Platform: AWS Glue, Amazon Redshift, Amazon S3, AWS Lambda, Amazon Kinesis, and AWS Step Functions.\n\nProficiency in Python and SQL for large-scale data processing and transformation.\nSolid understanding of data modeling, medallion architecture, and lakehouse principles.\nFamiliarity with CI/CD pipelines, DevOps, and version control (e.g., Git, AWS CodePipeline).\nKnowledge of data governance, lineage, and observability tools.\nExperience with performance optimization, cost control, and best practices in cloud environments.\nEducation (if blank, degree and/or field of study not specified)\nDegrees/Field of Study required:Degrees/Field of Study preferred:Certifications (if blank, certifications not specified)\nRequired Skills\nOptional Skills\nAccepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}Desired Languages (If blank, desired languages not specified)\nTravel Requirements\nNot SpecifiedAvailable for Work Visa Sponsorship?\nNoGovernment Clearance Required?\nNoJob Posting End 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