{"id":1229834,"url":"https://alion.io/job/pyramidci-databricks-data-architectlead-data-engineer","title":"Databricks Data Architect/Lead Data Engineer","company":{"id":2187693,"name":"Pyramid Consulting","domain":"pyramidci.com","url":"https://alion.io/company/pyramidci","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":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India","Chennai, India","Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":26000,"max_usd":47000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CircleCI","optional":false},{"name":"Databricks","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":"Scrum","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-09-22T04:51:43Z","employer_posted_date":null,"last_verified_at":"2026-09-22T04:51:43Z","board_verified":false,"closed_at":null,"days_open":9,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":9},"description":"We are looking for an experienced Databricks Data Architect / Lead Data Engineer with strong expertise in Data Warehousing, ETL, Databricks, Cloud Data Platforms, and Data Engineering. The ideal candidate should have extensive experience delivering large-scale data and analytics solutions, with strong hands-on expertise in Databricks, SQL, Python, PySpark, AWS/Azure, and modern data architecture.\n\nThe candidate must have strong experience in the BFSI (Banking, Financial Services & Insurance) domain, preferably with hands-on experience working on Banking projects, financial data platforms, regulatory reporting, customer/account data, transactions, risk, compliance, or related banking data solutions.\n\nRoles and Responsibilities :\n\n- Design and develop modern Data Warehouse and Data Lakehouse solutions using Databricks and cloud platforms such as AWS and Azure.\n\n- Define and implement scalable, high-performance data architecture and data engineering solutions aligned with business and analytical requirements.\n\n- Provide forward-thinking and innovative solutions in the Data Engineering, Data Analytics, and Data Platform space.\n\n- Collaborate with Data Warehouse, BI, Business, and Technical Leads to understand requirements for new ETL/data pipeline development.\n\n- Design, develop, and maintain robust ETL/ELT pipelines for batch and near-real-time/streaming data processing.\n\n- Develop data transformation processes using SQL, Python, PySpark, Spark, and Databricks.\n\n- Build and optimize Delta Lake/Lakehouse architectures, including ingestion, transformation, storage, and consumption layers.\n\n- Work closely with business stakeholders to understand reporting requirements and translate them into effective data models and reporting-layer solutions.\n\n- Analyze and triage production issues, identify gaps in existing pipelines, perform root-cause analysis, and implement permanent fixes.\n\n- Monitor and troubleshoot ETL/data pipelines, ensuring data quality, availability, reliability, and performance.\n\n- Orchestrate data pipelines using Apache Airflow and integrate workflows with cloud and Databricks platforms.\n\n- Implement data engineering solutions using batch and streaming technologies, including Kafka and AWS Kinesis, where applicable.\n\n- Drive technical discussions with client architects, business stakeholders, engineering teams, and other technical leads.\n\n- Participate in solution architecture, technical design, code reviews, performance optimization, and implementation discussions.\n\n- Mentor and support junior/entry-level team members in resolving technical challenges and production issues.\n\n- Provide technical guidance and help establish engineering best practices, coding standards, and reusable frameworks.\n\n- Work within a DevOps/CI-CD environment using tools such as Git, Terraform, CircleCI, and related technologies.\n\n- Implement and support data governance, data management, security, metadata, and data quality practices.\n\n- Work with modern Databricks capabilities including Unity Catalog, Delta Lake, data sharing, and related Data & AI platform capabilities.\n\n- Collaborate with cross-functional Agile teams and actively participate in Scrum ceremonies, sprint planning, estimation, technical discussions, and retrospectives.\n\n- Support performance tuning of complex SQL queries, Spark jobs, ETL pipelines, and data warehouse processes.\n\n- Ensure solutions adhere to enterprise architecture, security, compliance, and data governance standards, particularly within the BFSI/Banking environment.\n\nExperience :\n\n- 13+ years of overall experience in Data & Analytics, with strong experience in Data Engineering/Data Warehousing.\n\n- Experience delivering at least 2 large-scale, end-to-end Data Warehouse/Data Engineering implementations.\n\n- Strong experience in BFSI/Banking domain projects is mandatory.\n\n- Proven experience in technical leadership, solution design, architecture, and client-facing technical discussions.\n\n- Strong communication, stakeholder management, presentation, and technical leadership skills.\n\nEducation :\n\n- Bachelor's and/or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.\n\n- Equivalent professional experience may be considered.\nSkills\nData Architect, Data Engineering, Databricks, ETL, AWS, SQL, Python, Data Warehousing, PySpark, Apache Airflow","description_format":"text","description_chars":4384,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-25T14:00:00Z"}],"liveness":{"score":45,"band":"ok","label":"Likely open","p_open":1,"p_active":0.477,"p_room":0.945,"age_days":9,"expected_fill_days":24,"reasons":["seen:9","agency","velocity","win:mid"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/pyramidci-databricks-data-architectlead-data-engineer","json_url":"https://alion.io/job/pyramidci-databricks-data-architectlead-data-engineer.json","meta":{"generated_at":"2026-10-01T18:54:53Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1123,"day_limit":5000,"remaining_today":3877,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}